Course  Section  Title  Days  Time  Location  

CISC 130  01  IntroProgram&Prob SolvingSci  See Details  *  *  
Description of course Genetics B/ Lab: 
CRN: 40819
4 Credit Hours
Instructor: Scott C. Yilek
(Formerly QMCS 130 and 230) Introduction to problem solving with computers, using programming languages common to science and engineering disciplines; logical thinking, design and implementation of algorithms; and basic programming structures. Introduction to hardware and software: how computers acquire, store, process, and output information; how computer systems are designed, programmed, and tested. Students will use both a scientific programming language and an application package designed to implement programming features at a level more accessible to nonprogrammers. This course is designed for students majoring in Engineering or the sciences. Majors in the Department of Computer and Information Sciences should take CISC 131. Please see your academic advisor to ensure you select the appropriate class. Lab included. NOTE: Students who receive credit for CISC 130 may not receive credit for CISC 131
Schedule Details


CISC 130  02  IntroProgram.&Prob Solv.Sci  See Details  *  *  
Description of course Genetics B/ Lab: 
CRN: 40820
4 Credit Hours
Instructor: Keith L. Berrier
(Formerly QMCS 130 and 230) Introduction to problem solving with computers, using programming languages common to science and engineering disciplines; logical thinking, design and implementation of algorithms; and basic programming structures. Introduction to hardware and software: how computers acquire, store, process, and output information; how computer systems are designed, programmed, and tested. Students will use both a scientific programming language and an application package designed to implement programming features at a level more accessible to nonprogrammers. This course is designed for students majoring in Engineering or the sciences. Majors in the Department of Computer and Information Sciences should take CISC 131. Please see your academic advisor to ensure you select the appropriate class. Lab included. NOTE: Students who receive credit for CISC 130 may not receive credit for CISC 131
Schedule Details


CISC 130  03  IntroProgram&Prob SolvingSci  See Details  *  *  
Description of course Genetics B/ Lab: 
CRN: 40821
4 Credit Hours
Instructor: Ann K. Lockwood
(Formerly QMCS 130 and 230) Introduction to problem solving with computers, using programming languages common to science and engineering disciplines; logical thinking, design and implementation of algorithms; and basic programming structures. Introduction to hardware and software: how computers acquire, store, process, and output information; how computer systems are designed, programmed, and tested. Students will use both a scientific programming language and an application package designed to implement programming features at a level more accessible to nonprogrammers. This course is designed for students majoring in Engineering or the sciences. Majors in the Department of Computer and Information Sciences should take CISC 131. Please see your academic advisor to ensure you select the appropriate class. Lab included. NOTE: Students who receive credit for CISC 130 may not receive credit for CISC 131
Schedule Details


CISC 130  04  IntroProgram&Prob SolvingSci  See Details  *  *  
Description of course Genetics B/ Lab: 
CRN: 41059
4 Credit Hours
Instructor: Keith L. Berrier
(Formerly QMCS 130 and 230) Introduction to problem solving with computers, using programming languages common to science and engineering disciplines; logical thinking, design and implementation of algorithms; and basic programming structures. Introduction to hardware and software: how computers acquire, store, process, and output information; how computer systems are designed, programmed, and tested. Students will use both a scientific programming language and an application package designed to implement programming features at a level more accessible to nonprogrammers. This course is designed for students majoring in Engineering or the sciences. Majors in the Department of Computer and Information Sciences should take CISC 131. Please see your academic advisor to ensure you select the appropriate class. Lab included. NOTE: Students who receive credit for CISC 130 may not receive credit for CISC 131
Schedule Details


CISC 130  05  IntroProgram&Prob SolvingSci  See Details  *  *  
Description of course Genetics B/ Lab: 
CRN: 41153
4 Credit Hours
Instructor: Jason E. Sawin
(Formerly QMCS 130 and 230) Introduction to problem solving with computers, using programming languages common to science and engineering disciplines; logical thinking, design and implementation of algorithms; and basic programming structures. Introduction to hardware and software: how computers acquire, store, process, and output information; how computer systems are designed, programmed, and tested. Students will use both a scientific programming language and an application package designed to implement programming features at a level more accessible to nonprogrammers. This course is designed for students majoring in Engineering or the sciences. Majors in the Department of Computer and Information Sciences should take CISC 131. Please see your academic advisor to ensure you select the appropriate class. Lab included. NOTE: Students who receive credit for CISC 130 may not receive credit for CISC 131
Schedule Details


CISC 130  06  IntroProg&Prob SolviSci/wlab  M  W      1730  2015  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 41267
4 Credit Hours
Instructor: Jeffrey M. Thompson
(Formerly QMCS 130 and 230) Introduction to problem solving with computers, using programming languages common to science and engineering disciplines; logical thinking, design and implementation of algorithms; and basic programming structures. Introduction to hardware and software: how computers acquire, store, process, and output information; how computer systems are designed, programmed, and tested. Students will use both a scientific programming language and an application package designed to implement programming features at a level more accessible to nonprogrammers. This course is designed for students majoring in Engineering or the sciences. Majors in the Department of Computer and Information Sciences should take CISC 131. Please see your academic advisor to ensure you select the appropriate class. Lab included. NOTE: Students who receive credit for CISC 130 may not receive credit for CISC 131
Schedule Details


CISC 131  01  IntroProgramming&Prob Solving  See Details  *  *  
Description of course Genetics B/ Lab: 
CRN: 41932
4 Credit Hours
Instructor: Patrick L. Jarvis
This course is designed for students with majors in the Department of Computer and Information Sciences and focuses on logical thinking, the design and implementation of algorithms in a procedural language, testing, correctness, and the use of common programming structures such as arrays. In addition, basic machine concepts are covered including hardware organization and representation of information in the machine. The typical student will be adept at using the computer but will have no prior programming experience. Engineering and science majors should take CISC 130. Please see your academic advisor to ensure you select the appropriate class. Lab included. NOTE: Students who receive credit for CISC 131 may not receive credit for CISC 130
Schedule Details


CISC 131  02  IntroProgramming&Prob Solving  See Details  *  *  
Description of course Genetics B/ Lab: 
CRN: 43303
4 Credit Hours
Instructor: Scott C. Yilek
This course is designed for students with majors in the Department of Computer and Information Sciences and focuses on logical thinking, the design and implementation of algorithms in a procedural language, testing, correctness, and the use of common programming structures such as arrays. In addition, basic machine concepts are covered including hardware organization and representation of information in the machine. The typical student will be adept at using the computer but will have no prior programming experience. Engineering and science majors should take CISC 130. Please see your academic advisor to ensure you select the appropriate class. Lab included. NOTE: Students who receive credit for CISC 131 may not receive credit for CISC 130
Schedule Details


CISC 200  01  IntroComputer Tech & Bus Appl  M  W  F    1215  1320  OSS 432  
Description of course Genetics B/ Lab: 
CRN: 40822
4 Credit Hours
Instructor: Sarah R. Bowe
(Formerly QMCS 200) This course will prepare students to use computers in a business environment and in daily life. It will provide an introduction to programming and problem solving for nonmajors. Spreadsheet and database software will be used to solve problems related to business. The course includes an overview of hardware and software, how computers acquire and process information, and related topics.
NOTE: Students who receive credit for CISC 200 may not receive credit for CISC 110 or 216.
Schedule Details


CISC 200  02  IntroComputer Tech & Bus Appl  M  W  F    0935  1040  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 40823
4 Credit Hours
Instructor: Sarah R. Bowe
(Formerly QMCS 200) This course will prepare students to use computers in a business environment and in daily life. It will provide an introduction to programming and problem solving for nonmajors. Spreadsheet and database software will be used to solve problems related to business. The course includes an overview of hardware and software, how computers acquire and process information, and related topics.
NOTE: Students who receive credit for CISC 200 may not receive credit for CISC 110 or 216.
Schedule Details


CISC 200  03  IntroComputer Tech & Bus Appl   T  R     1525  1700  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 41933
4 Credit Hours
Instructor: John A. Daley
(Formerly QMCS 200) This course will prepare students to use computers in a business environment and in daily life. It will provide an introduction to programming and problem solving for nonmajors. Spreadsheet and database software will be used to solve problems related to business. The course includes an overview of hardware and software, how computers acquire and process information, and related topics.
NOTE: Students who receive credit for CISC 200 may not receive credit for CISC 110 or 216.
Schedule Details


CISC 230  01  Object Oriented Design & Prog  See Details  *  *  
Description of course Genetics B/ Lab: 
CRN: 40826
4 Credit Hours
Instructor: Patrick L. Jarvis
(Formerly QMCS 281) Programming and problem solving using an objectoriented approach. Builds on the procedural language foundation developed in CISC 130 or 131. Topics include: how procedural design differs from objectoriented design, algorithms, modeling, design requirements and representation, Uniform Modeling Language specification, implementation of objectoriented models, testing, and verification, and elementary design patterns. Lab included
Prerequisites: A minimum grade of C in CISC 130 or 131
Schedule Details


CISC 231  01  Data StructuresObject Design  M  W  F    1055  1200  OSS 333  
Description of course Genetics B/ Lab: 
CRN: 40824
4 Credit Hours
Instructor: Jason E. Sawin
(Formerly QMCS 350) Presents the fundamental suite of data structures and the algorithms used to implement them. Topics include: abstract data types, algorithm development and representation, searching, sorting, stacks, queues, lists, trees, measuring algorithm complexity, objectoriented design and implementation of moderately large and complex systems. Course assumes the student has proficiency in objectoriented specification, design, and implementation. Prerequisites: A minimum grade of C in CISC 230, MATH 128
Schedule Details


CISC 270  01  Web Management   T  R     1525  1700  OSS 432  
Description of course Genetics B/ Lab: 
CRN: 40827
4 Credit Hours
Instructor: Todd R. Hansen
(Formerly QMCS 310) This course will introduce students to the many technical and nontechnical issues related to designing and constructing an effective World Wide Web (WWW) site. Students will be introduced to the Internet and the WWW, how they function, and what they do. The course will cover basic relational database principles and introduce the various tools necessary to implement an electronic commerce (ecommerce) WWW site. Students will work in small teams, using their own WWW server, and develop a fully functional site using many of the tools introduced in the course.
Prerequisite: A minimum grade of C in CISC 230
Schedule Details


CISC 297  01  TOPICS:Bus.Appl.Prob.Sol.&Prog   T  R     1330  1510  OSS 428  
Description of course Genetics B/ Lab: 
CRN: 43198
4 Credit Hours
Instructor: Patrick L. Jarvis
This course will prepare students to use computers in a business environment and daily life. It will provide an introduction to programming and problem solving for nonmajors with emphasis on problems drawn from the area of actuarial science. Students will learn both a programming language and an application package designed to implement programming features in a manner more accessible to nonprogrammers. The course includes an overview of hardware and software, how computers acquire and process information, and related topics.
This course is for ACSC majors only; or by permission of the instructor.
Schedule Details


CISC 310  01  Operating Systems  M  W      1525  1700  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 40991
4 Credit Hours
Instructor: Ann K. Lockwood
(Formerly QMCS 360) The basic principles of designing and building operating systems. Sequential versus concurrent processes, synchronization and mutual exclusion, memory management techniques, CPU scheduling, input/output device handling, file systems design, security and protection. Prerequisite: A minimum grade of C in CISC 230
Schedule Details


CISC 321  01  Systems Analysis and Design II   T  R     0800  0940  OSS 415  
Description of course Genetics B/ Lab: 
CRN: 40843
4 Credit Hours
Instructor: Timothy G. Meyer
(Formerly QMCS 421) Continuation of CISC 320. Concentration on usercentered design (UCD), physical design, low and high fidelity prototyping, and agile methods. Emphasis on managerial problems in systems development. Continued use of CASE and projectmanagement tools. A "real world" design and prototyping project is an integral part of this course. Prerequisite: CISC 320
Schedule Details


CISC 410  01  Advanced Information Security  M  W  F    1335  1440  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 41439
4 Credit Hours
Instructor: Scott C. Yilek
A more indepth study of security issues than CISC 210. This course will focus on modern attack techniques and defenses in the areas of application security, network security, cryptographic protocols, and web security. Prerequisite: A minimum grade of C in CISC 210
Schedule Details


CISC 419  01  Accounting Information Systems  M  W      1525  1700  OSS 432  
Description of course Genetics B/ Lab: 
CRN: 40825
4 Credit Hours
Instructor: Chelley M. Vician
(Formerly QMCS 419) This course will provide an understanding of the conceptual framework and practices of accounting information systems and the ability to work effectively with computer specialists and management to design, implement and audit such systems. Examples of subjects included are: systems development life cycle (SDLC), systems analysis phase of the SDLC, data and process models, operations of a corporate data center, including internal controls, database integrity, audit considerations for both internal and external auditors, unit integration, and system testing. Prerequisites: CISC 110 or 200, and previous or concurrent enrollment in ACCT 316
Schedule Details


CISC 419  02  Accounting Information Systems  M  W      1730  1915  OSS 432  
Description of course Genetics B/ Lab: 
CRN: 43215
4 Credit Hours
Instructor: Chelley M. Vician
(Formerly QMCS 419) This course will provide an understanding of the conceptual framework and practices of accounting information systems and the ability to work effectively with computer specialists and management to design, implement and audit such systems. Examples of subjects included are: systems development life cycle (SDLC), systems analysis phase of the SDLC, data and process models, operations of a corporate data center, including internal controls, database integrity, audit considerations for both internal and external auditors, unit integration, and system testing. Prerequisites: CISC 110 or 200, and previous or concurrent enrollment in ACCT 316
Schedule Details


CISC 450  01  Database Design I  M  W  F    0935  1040  OSS 333  
Description of course Genetics B/ Lab: 
CRN: 40992
4 Credit Hours
Instructor: Jason E. Sawin
(Formerly QMCS 450) Introduction to database management systems design philosophy. Design considerations for satisfying both availability and integrity requirements. Data models used to structure the logical view of the database. Schema, subschemas, and database administration. Emphasis on general purpose relational database management systems using SQL.
Prerequisite: a minimum grade of C in CISC 230
Schedule Details

Course  Section  Title  Days  Time  Location  

CISC 130  01  IntroProgram&Prob SolvingSci   T W R F    0830  1300  OSS 327  
Description of course Genetics B/ Lab: 
CRN: 10316
4 Credit Hours
Instructor: Keith L. Berrier
(Formerly QMCS 130 and 230) Introduction to problem solving with computers, using programming languages common to science and engineering disciplines; logical thinking, design and implementation of algorithms; and basic programming structures. Introduction to hardware and software: how computers acquire, store, process, and output information; how computer systems are designed, programmed, and tested. Students will use both a scientific programming language and an application package designed to implement programming features at a level more accessible to nonprogrammers. This course is designed for students majoring in Engineering or the sciences. Majors in the Department of Computer and Information Sciences should take CISC 131. Please see your academic advisor to ensure you select the appropriate class. Lab included. NOTE: Students who receive credit for CISC 130 may not receive credit for CISC 131
Schedule Details


CISC 200  01  IntroComputer Tech & Bus Appl   T W R F    1000  1300  OSS 432  
Description of course Genetics B/ Lab: 
CRN: 10040
4 Credit Hours
Instructor: John A. Daley
(Formerly QMCS 200) This course will prepare students to use computers in a business environment and in daily life. It will provide an introduction to programming and problem solving for nonmajors. Spreadsheet and database software will be used to solve problems related to business. The course includes an overview of hardware and software, how computers acquire and process information, and related topics.
NOTE: Students who receive credit for CISC 200 may not receive credit for CISC 110 or 216.
Schedule Details


CISC 200  02  IntroComputer Tech & Bus Appl  See Details  *  *  
Description of course Genetics B/ Lab: 
CRN: 10108
4 Credit Hours
Instructor: John A. Daley
(Formerly QMCS 200) This course will prepare students to use computers in a business environment and in daily life. It will provide an introduction to programming and problem solving for nonmajors. Spreadsheet and database software will be used to solve problems related to business. The course includes an overview of hardware and software, how computers acquire and process information, and related topics.
NOTE: Students who receive credit for CISC 200 may not receive credit for CISC 110 or 216.
Schedule Details

Course  Section  Title  Days  Time  Location  

CISC 120  01  Computers in Elementary Educ  M  W  F    1335  1440  OSS 428  
Description of course Genetics B/ Lab: 
CRN: 20720
4 Credit Hours
Instructor: Mark E. Werness
(Formerly QMCS 120) This course is intended for elementary education majors. Topics include the role of the computer in elementary and middleschool education, computer applications in science and mathematics, data analysis, software packages for use in elementary and middleschool classrooms, ComputerAssistedInstruction (CAI), multimedia, electronic portfolios, telecommunication and software creation using tools such as MicroWorlds, Scratch, and HTML. This course fulfills the third course in the Natural Science and Mathematical and Quantative Reasoning. Prerequisite: Elementary Education or SMEE major
Schedule Details


CISC 130  01  IntroProgram&Prob SolvingSci  See Details  *  *  
Description of course Genetics B/ Lab: 
CRN: 20721
4 Credit Hours
Instructor: Scott C. Yilek
(Formerly QMCS 130 and 230) Introduction to problem solving with computers, using programming languages common to science and engineering disciplines; logical thinking, design and implementation of algorithms; and basic programming structures. Introduction to hardware and software: how computers acquire, store, process, and output information; how computer systems are designed, programmed, and tested. Students will use both a scientific programming language and an application package designed to implement programming features at a level more accessible to nonprogrammers. This course is designed for students majoring in Engineering or the sciences. Majors in the Department of Computer and Information Sciences should take CISC 131. Please see your academic advisor to ensure you select the appropriate class. Lab included. NOTE: Students who receive credit for CISC 130 may not receive credit for CISC 131
Schedule Details


CISC 130  02  IntroProgram&Prob SolvingSci  See Details  *  *  
Description of course Genetics B/ Lab: 
CRN: 20722
4 Credit Hours
Instructor: Jason E. Sawin
(Formerly QMCS 130 and 230) Introduction to problem solving with computers, using programming languages common to science and engineering disciplines; logical thinking, design and implementation of algorithms; and basic programming structures. Introduction to hardware and software: how computers acquire, store, process, and output information; how computer systems are designed, programmed, and tested. Students will use both a scientific programming language and an application package designed to implement programming features at a level more accessible to nonprogrammers. This course is designed for students majoring in Engineering or the sciences. Majors in the Department of Computer and Information Sciences should take CISC 131. Please see your academic advisor to ensure you select the appropriate class. Lab included. NOTE: Students who receive credit for CISC 130 may not receive credit for CISC 131
Schedule Details


CISC 130  03  IntroProgram&Prob SolvingSci  See Details  *  *  
Description of course Genetics B/ Lab: 
CRN: 20809
4 Credit Hours
Instructor: Jason E. Sawin
(Formerly QMCS 130 and 230) Introduction to problem solving with computers, using programming languages common to science and engineering disciplines; logical thinking, design and implementation of algorithms; and basic programming structures. Introduction to hardware and software: how computers acquire, store, process, and output information; how computer systems are designed, programmed, and tested. Students will use both a scientific programming language and an application package designed to implement programming features at a level more accessible to nonprogrammers. This course is designed for students majoring in Engineering or the sciences. Majors in the Department of Computer and Information Sciences should take CISC 131. Please see your academic advisor to ensure you select the appropriate class. Lab included. NOTE: Students who receive credit for CISC 130 may not receive credit for CISC 131
Schedule Details


CISC 130  04  IntroProgram&Prob SolvingSci  See Details  *  *  
Description of course Genetics B/ Lab: 
CRN: 20807
4 Credit Hours
Instructor: Ann K. Lockwood
(Formerly QMCS 130 and 230) Introduction to problem solving with computers, using programming languages common to science and engineering disciplines; logical thinking, design and implementation of algorithms; and basic programming structures. Introduction to hardware and software: how computers acquire, store, process, and output information; how computer systems are designed, programmed, and tested. Students will use both a scientific programming language and an application package designed to implement programming features at a level more accessible to nonprogrammers. This course is designed for students majoring in Engineering or the sciences. Majors in the Department of Computer and Information Sciences should take CISC 131. Please see your academic advisor to ensure you select the appropriate class. Lab included. NOTE: Students who receive credit for CISC 130 may not receive credit for CISC 131
Schedule Details


CISC 130  05  IntroProgram&Prob SolvingSci   T  R     1730  2015  OSS 428  
Description of course Genetics B/ Lab: 
CRN: 20989
4 Credit Hours
Instructor: Keith L. Berrier
(Formerly QMCS 130 and 230) Introduction to problem solving with computers, using programming languages common to science and engineering disciplines; logical thinking, design and implementation of algorithms; and basic programming structures. Introduction to hardware and software: how computers acquire, store, process, and output information; how computer systems are designed, programmed, and tested. Students will use both a scientific programming language and an application package designed to implement programming features at a level more accessible to nonprogrammers. This course is designed for students majoring in Engineering or the sciences. Majors in the Department of Computer and Information Sciences should take CISC 131. Please see your academic advisor to ensure you select the appropriate class. Lab included. NOTE: Students who receive credit for CISC 130 may not receive credit for CISC 131
Schedule Details


CISC 131  01  IntroProgramming&Prob Solving  See Details  *  *  
Description of course Genetics B/ Lab: 
CRN: 20723
4 Credit Hours
Instructor: Patrick L. Jarvis
This course is designed for students with majors in the Department of Computer and Information Sciences and focuses on logical thinking, the design and implementation of algorithms in a procedural language, testing, correctness, and the use of common programming structures such as arrays. In addition, basic machine concepts are covered including hardware organization and representation of information in the machine. The typical student will be adept at using the computer but will have no prior programming experience. Engineering and science majors should take CISC 130. Please see your academic advisor to ensure you select the appropriate class. Lab included. NOTE: Students who receive credit for CISC 131 may not receive credit for CISC 130
Schedule Details


CISC 200  01  IntroComputer Tech & Bus Appl   T  R     1330  1510  OSS 428  
Description of course Genetics B/ Lab: 
CRN: 20724
4 Credit Hours
Instructor: Staff
(Formerly QMCS 200) This course will prepare students to use computers in a business environment and in daily life. It will provide an introduction to programming and problem solving for nonmajors. Spreadsheet and database software will be used to solve problems related to business. The course includes an overview of hardware and software, how computers acquire and process information, and related topics.
NOTE: Students who receive credit for CISC 200 may not receive credit for CISC 110 or 216.
Schedule Details


CISC 200  02  IntroComputer Tech & Bus Appl   T  R     1525  1700  OSS 432  
Description of course Genetics B/ Lab: 
CRN: 20725
4 Credit Hours
Instructor: Staff
(Formerly QMCS 200) This course will prepare students to use computers in a business environment and in daily life. It will provide an introduction to programming and problem solving for nonmajors. Spreadsheet and database software will be used to solve problems related to business. The course includes an overview of hardware and software, how computers acquire and process information, and related topics.
NOTE: Students who receive credit for CISC 200 may not receive credit for CISC 110 or 216.
Schedule Details


CISC 200  03  IntroComputer Tech & Bus Appl  M        1730  2100  OSS 428  
Description of course Genetics B/ Lab: 
CRN: 21334
4 Credit Hours
Instructor: Sarah R. Bowe
(Formerly QMCS 200) This course will prepare students to use computers in a business environment and in daily life. It will provide an introduction to programming and problem solving for nonmajors. Spreadsheet and database software will be used to solve problems related to business. The course includes an overview of hardware and software, how computers acquire and process information, and related topics.
NOTE: Students who receive credit for CISC 200 may not receive credit for CISC 110 or 216.
Schedule Details


CISC 200  04  IntroComputer Tech & Bus Appl   T  R     0955  1135  OSS 432  
Description of course Genetics B/ Lab: 
CRN: 22350
4 Credit Hours
Instructor: Staff
(Formerly QMCS 200) This course will prepare students to use computers in a business environment and in daily life. It will provide an introduction to programming and problem solving for nonmajors. Spreadsheet and database software will be used to solve problems related to business. The course includes an overview of hardware and software, how computers acquire and process information, and related topics.
NOTE: Students who receive credit for CISC 200 may not receive credit for CISC 110 or 216.
Schedule Details


CISC 210  01  Information Security  M  W      1335  1510  OSS 432  
Description of course Genetics B/ Lab: 
CRN: 20749
4 Credit Hours
Instructor: Scott C. Yilek
An introductory course in computer security.
Topics include operating system security, cryptography, user authentication, application security, secure programming, web security and privacy issues, and ethical issues in the field of computer security. Emphasis is on understanding the technical aspects of how adversaries exploit systems and the techniques for defending against these attacks.
Prerequisites: 1) MATH 128 or ENGR 230 or STAT 220(IDTH 220) (may be taken concurrently), and 2) a minimum grade of C in CISC 130 or 131
Schedule Details


CISC 230  01  Object Oriented Design & Prog  See Details  *  *  
Description of course Genetics B/ Lab: 
CRN: 20726
4 Credit Hours
Instructor: Patrick L. Jarvis
(Formerly QMCS 281) Programming and problem solving using an objectoriented approach. Builds on the procedural language foundation developed in CISC 130 or 131. Topics include: how procedural design differs from objectoriented design, algorithms, modeling, design requirements and representation, Uniform Modeling Language specification, implementation of objectoriented models, testing, and verification, and elementary design patterns. Lab included
Prerequisites: A minimum grade of C in CISC 130 or 131
Schedule Details


CISC 230  02  Object Oriented Design & Prog  See Details  *  *  
Description of course Genetics B/ Lab: 
CRN: 22351
4 Credit Hours
Instructor: Mark E. Werness
(Formerly QMCS 281) Programming and problem solving using an objectoriented approach. Builds on the procedural language foundation developed in CISC 130 or 131. Topics include: how procedural design differs from objectoriented design, algorithms, modeling, design requirements and representation, Uniform Modeling Language specification, implementation of objectoriented models, testing, and verification, and elementary design patterns. Lab included
Prerequisites: A minimum grade of C in CISC 130 or 131
Schedule Details


CISC 320  01  Systems Analysis and Design I  M  W      1525  1700  OSS 333  
Description of course Genetics B/ Lab: 
CRN: 20731
4 Credit Hours
Instructor: Timothy G. Meyer
(Formerly QMCS 420) A study of systems analysis methodologies used in the analysis and design of information systems. Emphasis on data, process, and modeling by use of a CASE tool: entity relationship diagrams and data normalization, data flow diagrams, use case diagrams, and data dictionaries. This is a "hands on" course where students form teams to analyze the needs of a business client in the community. Prerequisite: A minimum grade of C in CISC 230
Schedule Details


CISC 325  01  ECommerce  M  W  F    1055  1200  OSS 428  
Description of course Genetics B/ Lab: 
CRN: 20727
4 Credit Hours
Instructor: Staff
(Formerly QMCS 425) A study of relevant technologies and how they are used in today's modern organizations to help manage the information resource of the organization. Emphasis is placed on the use of the Internet and World Wide Web and how they have changed organizational operations and strategies. This is an "active learning" course in which students will be researching current information systems technologies (such as Electronic Commerce [ecommerce]) and will be participating in the design and development of an ecommerce website for a fictitious organization. Prerequisite: A minimum grade of C in CISC 230
Schedule Details


CISC 340  01  Computer Architecture  M  W  F    1215  1320  OSS 432  
Description of course Genetics B/ Lab: 
CRN: 20777
4 Credit Hours
Instructor: Jason E. Sawin
(Formerly QMCS 300 and 340) Structure and organization of computer systems and components, including the design of central processors, memory, and input/output systems. Instruction sets and basic machine language programming. Prerequisites: CISC 231
Schedule Details


CISC 370  01  Computer Networking   T  R     1330  1510  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 20728
4 Credit Hours
Instructor: Patrick L. Jarvis
(Formerly QMCS 370) An introduction to computer networking. covering theory and implementation of basic networking concepts including communication protocols, local area networks, http protocol and clientserver and peertopeer computing. Prerequisites: A minimum grade of C in CISC 230
Schedule Details


CISC 419  01  Accounting Information Systems  M  W      1730  1915  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 20729
4 Credit Hours
Instructor: Suzette Allaire
(Formerly QMCS 419) This course will provide an understanding of the conceptual framework and practices of accounting information systems and the ability to work effectively with computer specialists and management to design, implement and audit such systems. Examples of subjects included are: systems development life cycle (SDLC), systems analysis phase of the SDLC, data and process models, operations of a corporate data center, including internal controls, database integrity, audit considerations for both internal and external auditors, unit integration, and system testing. Prerequisites: CISC 110 or 200, and previous or concurrent enrollment in ACCT 316
Schedule Details


CISC 419  02  Accounting Information Systems   T  R     1525  1700  OSS 333  
Description of course Genetics B/ Lab: 
CRN: 20730
4 Credit Hours
Instructor: Ann K. Staelgraeve
(Formerly QMCS 419) This course will provide an understanding of the conceptual framework and practices of accounting information systems and the ability to work effectively with computer specialists and management to design, implement and audit such systems. Examples of subjects included are: systems development life cycle (SDLC), systems analysis phase of the SDLC, data and process models, operations of a corporate data center, including internal controls, database integrity, audit considerations for both internal and external auditors, unit integration, and system testing. Prerequisites: CISC 110 or 200, and previous or concurrent enrollment in ACCT 316
Schedule Details


CISC 419  03  Accounting Information Systems   T  R     1730  1915  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 20808
4 Credit Hours
Instructor: Staff
(Formerly QMCS 419) This course will provide an understanding of the conceptual framework and practices of accounting information systems and the ability to work effectively with computer specialists and management to design, implement and audit such systems. Examples of subjects included are: systems development life cycle (SDLC), systems analysis phase of the SDLC, data and process models, operations of a corporate data center, including internal controls, database integrity, audit considerations for both internal and external auditors, unit integration, and system testing. Prerequisites: CISC 110 or 200, and previous or concurrent enrollment in ACCT 316
Schedule Details


CISC 440  01  Artfcl Intelligence & Robotics  M  W      1335  1510  OSS 415  
Description of course Genetics B/ Lab: 
CRN: 22647
4 Credit Hours
Instructor: Ann K. Lockwood
(Formerly QMCS 380) Theory and implementation techniques using computers to solve problems, play games, prove theorems, recognize patterns, create artwork and musical scores, translate languages, read handwriting, speak and perform mechanical assembly. Emphasis placed on implementation of these techniques in robots. Prerequisites: CISC 230 and STAT 220 (IDTH 220)
Schedule Details

Course  Section  Title  Days  Time  Location  

STAT 220  01  Statistics I  M  W  F    0815  0920  OSS 313  
Description of course Genetics B/ Lab: 
CRN: 41139
4 Credit Hours
Instructor: Erin M. Curran
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  02  Statistics I  M  W  F    0815  0920  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 41140
4 Credit Hours
Instructor: Marc D. Isaacson
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  03  Statistics I  M  W  F    0935  1040  OSS 313  
Description of course Genetics B/ Lab: 
CRN: 41141
4 Credit Hours
Instructor: Erin M. Curran
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  04  Statistics I  M  W  F    0935  1040  OEC 206  
Description of course Genetics B/ Lab: 
CRN: 41142
4 Credit Hours
Instructor: Mark E. Werness
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  05  Statistics I  M  W  F    1055  1200  OEC 206  
Description of course Genetics B/ Lab: 
CRN: 41143
4 Credit Hours
Instructor: Mark E. Werness
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  06  Statistics I  M  W  F    1055  1200  OSS 432  
Description of course Genetics B/ Lab: 
CRN: 41144
4 Credit Hours
Instructor: Agnes Kiss
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  07  Statistics I  M  W  F    1215  1320  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 41145
4 Credit Hours
Instructor: Leigh Lawton
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  08  Statistics I  M  W  F    1335  1440  OSS 432  
Description of course Genetics B/ Lab: 
CRN: 41146
4 Credit Hours
Instructor: Leigh Lawton
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  09  Statistics I   T  R     0800  0940  OSS 313  
Description of course Genetics B/ Lab: 
CRN: 41147
Instructor: German J. Pliego Hernandez
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  10  Statistics I   T  R     0800  0940  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 41148
4 Credit Hours
Instructor: David L. Ehren
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  11  Statistics I   T  R     0955  1135  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 41149
4 Credit Hours
Instructor: David L. Ehren
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  12  Statistics I   T  R     0955  1135  OSS 329  
Description of course Genetics B/ Lab: 
CRN: 41150
4 Credit Hours
Instructor: German J. Pliego Hernandez
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  13  Statistics I   T  R     1330  1510  OSS 329  
Description of course Genetics B/ Lab: 
CRN: 41151
4 Credit Hours
Instructor: Daniel G. Brick
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  14  Statistics I   T  R     1330  1510  OSS 313  
Description of course Genetics B/ Lab: 
CRN: 41440
4 Credit Hours
Instructor: German J. Pliego Hernandez
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  15  Statistics I   T  R     1525  1700  OSS 329  
Description of course Genetics B/ Lab: 
CRN: 41152
4 Credit Hours
Instructor: Daniel G. Brick
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  16  Statistics I   T  R     1730  1915  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 41441
4 Credit Hours
Instructor: Agnes Kiss
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 314  01  Mathematical Statistics   T  R     0955  1135  OSS 214  
Description of course Genetics B/ Lab: 
CRN: 41216
4 Credit Hours
Instructor: Arkady Shemyakin
Populations and random sampling; sampling distributions. Theory of statistical estimation; criteria and methods of point and interval estimation. Theory of testing statistical hypotheses; nonparametric methods. Offered in fall semester. Prerequisite: MATH 240 and 313 NOTE: Students who recieve credit for MATH 314 may not receive credit for MATH 303.
Schedule Details


STAT 314  02  Mathematical Statistics   T  R     1525  1700  OSS 227  
Description of course Genetics B/ Lab: 
CRN: 41713
4 Credit Hours
Instructor: Arkady Shemyakin
Populations and random sampling; sampling distributions. Theory of statistical estimation; criteria and methods of point and interval estimation. Theory of testing statistical hypotheses; nonparametric methods. Offered in fall semester. Prerequisite: MATH 240 and 313 NOTE: Students who recieve credit for MATH 314 may not receive credit for MATH 303.
Schedule Details


STAT 320  01  Statistics II  M  W  F    1215  1320  OSS 333  
Description of course Genetics B/ Lab: 
CRN: 43197
4 Credit Hours
Instructor: Erin M. Curran
Formerly IDTH 320 or QMCS 320 Applie linear regression models. Simple linear regression; introduction, inferences, diagonstics, remedial measures, simultaneous inference. Matrix approach in linear regression. Multiple regression; inference, remedial measures, extra sums of squares, partial determinations, standardized models, use of indicator and mixed variables, polynomial regression, model selection and validation, diagnostics, remedial measures, multicollinearity and effects, autocorrelation. Single and multifactor analysis of variance: analysis of factor level means, interactions, inferences, diagnostics and remedial measures. A statistical package must be used as tool. Optional topics may include: logistic regression, design of experiments, and forecasting. Prerequisite: STAT 202 or 333 or IDTH 201 or 220 or MATH 333
Schedule Details

Course  Section  Title  Days  Time  Location  

STAT 201  01  Introductory Statistics II   T  R     1400  1700  OSS 313  
Description of course Genetics B/ Lab: 
CRN: 10109
2 Credit Hours
Instructor: German J. Pliego Hernandez
(Formerly IDTH 201) This course is for students desiring to satisfy the coverage of STAT 220 ( a full semester of statistics), when less than one full semester of statistics has been taken. Review of inferential statistics; sampling distribution of the sample mean and sample proprtion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Introduction to basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. Prerequsite: STAT 206 (IDTH 206) or at least .35 semester, but less than one semester of statistics. Note: Students who receive credit for STAT 201 may not receive credit for STAT 220.
Schedule Details


STAT 220  01  Statistics I   T W R F    0900  1200  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 10054
4 Credit Hours
Instructor: Agnes Kiss
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  02  Statistics I   T W R F    1000  1300  OSS 313  
Description of course Genetics B/ Lab: 
CRN: 10055
4 Credit Hours
Instructor: German J. Pliego Hernandez
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  03  Statistics I   T W R F    1615  1915  OSS 432  
Description of course Genetics B/ Lab: 
CRN: 10056
4 Credit Hours
Instructor: David L. Ehren
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details

Course  Section  Title  Days  Time  Location  

STAT 220  01  Statistics I  M  W  F    0815  0920  OSS 329  
Description of course Genetics B/ Lab: 
CRN: 20912
4 Credit Hours
Instructor: Marc D. Isaacson
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  02  Statistics I  M  W  F    0815  0920  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 20913
4 Credit Hours
Instructor: David L. Ehren
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  03  Statistics I  M  W  F    0935  1040  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 20914
4 Credit Hours
Instructor: David L. Ehren
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  04  Statistics I  M  W  F    0935  1040  OSS 329  
Description of course Genetics B/ Lab: 
CRN: 20915
4 Credit Hours
Instructor: Erin M. Curran
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  05  Statistics I  M  W  F    1055  1200  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 20916
4 Credit Hours
Instructor: David L. Ehren
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  06  Statistics I  M  W  F    1055  1200  OSS 328  
Description of course Genetics B/ Lab: 
CRN: 20917
4 Credit Hours
Instructor: Leigh Lawton
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  07  Statistics I  M  W      1525  1700  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 20918
4 Credit Hours
Instructor: Agnes Kiss
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  08  Statistics I  M  W      1730  1915  OSS 432  
Description of course Genetics B/ Lab: 
CRN: 20919
4 Credit Hours
Instructor: Agnes Kiss
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  09  Statistics I   T  R     0800  0940  OSS 431  
Description of course Genetics B/ Lab: 
CRN: 20920
4 Credit Hours
Instructor: Marc D. Isaacson
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  10  Statistics I   T  R     0800  0940  OSS 329  
Description of course Genetics B/ Lab: 
CRN: 20921
4 Credit Hours
Instructor: German J. Pliego Hernandez
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  11  Statistics I   T  R     0955  1135  OSS 313  
Description of course Genetics B/ Lab: 
CRN: 20922
4 Credit Hours
Instructor: German J. Pliego Hernandez
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  12  Statistics I   T  R     0955  1135  OSS 329  
Description of course Genetics B/ Lab: 
CRN: 20923
4 Credit Hours
Instructor: Daniel G. Brick
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  13  Statistics I   T  R     1330  1510  OSS 329  
Description of course Genetics B/ Lab: 
CRN: 20924
4 Credit Hours
Instructor: German J. Pliego Hernandez
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 220  14  Statistics I   T  R     1525  1700  OSS 329  
Description of course Genetics B/ Lab: 
CRN: 20925
4 Credit Hours
Instructor: Daniel G. Brick
Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chisquare, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201
Schedule Details


STAT 310  01  Biostatistics  M  W  F    1215  1320  OSS 428  
Description of course Genetics B/ Lab: 
CRN: 21336
4 Credit Hours
Instructor: Erin M. Curran
This course provides students with the knowledge and skils needed to effectively apply basic statistical methods in health related fields, such as Biology, Medicine, and Public Health. Students learn inferential statistical techniques involving topics in estimation, hypothesis testing, nonparametric methods, clinical trials, contingency tables, review of analysis of variance and linear regression, and a brief introduction to experimental design.
Schedule Details


STAT 314  01  Mathematical Statistics   T  R     1330  1510  OSS 227  
Description of course Genetics B/ Lab: 
CRN: 21674
4 Credit Hours
Instructor: Arkady Shemyakin
Populations and random sampling; sampling distributions. Theory of statistical estimation; criteria and methods of point and interval estimation. Theory of testing statistical hypotheses; nonparametric methods. Offered in fall semester. Prerequisite: MATH 240 and 313 NOTE: Students who recieve credit for MATH 314 may not receive credit for MATH 303.
Schedule Details


STAT 333  01  Applied Statistical Methods   T  R     0955  1135  OSS 214  
Description of course Genetics B/ Lab: 
CRN: 20911
4 Credit Hours
Instructor: Arkady Shemyakin
Regression and exponential smoothing methods; Stochastic Time Series: auto and crosscorrelation, autoregressive moving average models; application to forecasting. Prerequisites: MATH 303 or 314 or STAT 314 or permission of instructor
Schedule Details


STAT 333  02  Applied Statistical Methods   T  R     1525  1700  OSS 227  
Description of course Genetics B/ Lab: 
CRN: 21746
4 Credit Hours
Instructor: Arkady Shemyakin
Regression and exponential smoothing methods; Stochastic Time Series: auto and crosscorrelation, autoregressive moving average models; application to forecasting. Prerequisites: MATH 303 or 314 or STAT 314 or permission of instructor
Schedule Details
