Course Offerings
Below are courses offered in Computer and Information Sciences. For uptodate information regarding course information for registration, please visit Murphy Online.
JTerm 2017 Courses
Course  Section  Title  Days  Time  Location  

CISC 130  01  IntroProgram&Prob SolvingSci   T W R F    0830  1300  OSS 428  
Description of course Genetics B/ Lab: 
Days of Week: T W R F   Time of Day:0830  1300 Location:OSS 428 Course Registration Number:10164 (View in ClassFinder) Credit Hours:4 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    0900  1200  OSS 432  
Description of course Genetics B/ Lab: 
Days of Week: T W R F   Time of Day:0900  1200 Location:OSS 432 Course Registration Number:10030 (View in ClassFinder) Credit Hours:4 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   T W R F    1000  1300  OSS 431  
Description of course Genetics B/ Lab: 
Days of Week: T W R F   Time of Day:1000  1300 Location:OSS 431 Course Registration Number:10077 (View in ClassFinder) Credit Hours:4 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

Spring 2017 Courses
Course  Section  Title  Days  Time  Location  

CISC 120  01  Computers in Elementary Educ  M  W  F    1335  1440  OSS 429  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:1335  1440 Location:OSS 429 Course Registration Number:22365 (View in ClassFinder) Credit Hours:4 Instructor:Mark E. Werness 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 Quantitative Reasoning. Prerequisite: Elementary Education or SMEE major Schedule Details


CISC 130  02  IntroProgram&Prob SolvingSci  See Details  *  *  
Description of course Genetics B/ Lab: 
Days of Week:See Details Time of Day:* Location:* Course Registration Number:20619 (View in ClassFinder) Credit Hours:4 Instructor:Joseph M. Myre (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: 
Days of Week:See Details Time of Day:* Location:* Course Registration Number:20690 (View in ClassFinder) Credit Hours:4 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  04  IntroProgram&Prob SolvingSci  See Details  *  *  
Description of course Genetics B/ Lab: 
Days of Week:See Details Time of Day:* Location:* Course Registration Number:20688 (View in ClassFinder) Credit Hours:4 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  05  IntroProgram&Prob SolvingSci  See Details  *  *  
Description of course Genetics B/ Lab: 
Days of Week:See Details Time of Day:* Location:* Course Registration Number:20834 (View in ClassFinder) Credit Hours:4 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   T  R     1730  2015  OSS 428  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:1730  2015 Location:OSS 428 Course Registration Number:21738 (View in ClassFinder) Credit Hours:4 Instructor:Attila Magyar (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: 
Days of Week:See Details Time of Day:* Location:* Course Registration Number:20620 (View in ClassFinder) Credit Hours:4 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 131  02  IntroProgramming&Prob Solving  See Details  *  *  
Description of course Genetics B/ Lab: 
Days of Week:See Details Time of Day:* Location:* Course Registration Number:21739 (View in ClassFinder) Credit Hours:4 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 431  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:1215  1320 Location:OSS 431 Course Registration Number:20621 (View in ClassFinder) Credit Hours:4 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  03  IntroComputer Tech & Bus Appl   T  R     0955  1135  OSS 432  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:0955  1135 Location:OSS 432 Course Registration Number:21060 (View in ClassFinder) Credit Hours:4 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     1330  1510  OSS 428  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:1330  1510 Location:OSS 428 Course Registration Number:21318 (View in ClassFinder) Credit Hours:4 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  05  IntroComputer Tech & Bus Appl  M  W      1525  1700  OSS 432  
Description of course Genetics B/ Lab: 
Days of Week:M  W     Time of Day:1525  1700 Location:OSS 432 Course Registration Number:21755 (View in ClassFinder) Credit Hours:4 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  06  IntroComputer Tech & Bus Appl   T       1730  2100  OSS 432  
Description of course Genetics B/ Lab: 
Days of Week: T      Time of Day:1730  2100 Location:OSS 432 Course Registration Number:21756 (View in ClassFinder) Credit Hours:4 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 210  01  Information Security  M  W      1335  1510  OSS 432  
Description of course Genetics B/ Lab: 
Days of Week:M  W     Time of Day:1335  1510 Location:OSS 432 Course Registration Number:20641 (View in ClassFinder) Credit Hours:4 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: 
Days of Week:See Details Time of Day:* Location:* Course Registration Number:20623 (View in ClassFinder) Credit Hours:4 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: 
Days of Week:See Details Time of Day:* Location:* Course Registration Number:21319 (View in ClassFinder) Credit Hours:4 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 428  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:1055  1200 Location:OSS 428 Course Registration Number:21757 (View in ClassFinder) Credit Hours:4 Instructor:Sarah B. Miracle (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 298  01  Topics:Bus.Appl.Prob.Sol.&Pro   T  R     1525  1700  OSS 428  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:1525  1700 Location:OSS 428 Course Registration Number:22369 (View in ClassFinder) Credit Hours:4 Instructor:John A. Daley The subject matter of these courses will vary from year to year, but will not duplicate existing courses. Descriptions of these courses are available in the Searchable Class Schedule on Murphy Online, View Searchable Class Schedule Schedule Details


CISC 320  01  Systems Analysis and Design I  M  W      1525  1700  OSS 428  
Description of course Genetics B/ Lab: 
Days of Week:M  W     Time of Day:1525  1700 Location:OSS 428 Course Registration Number:20626 (View in ClassFinder) Credit Hours:4 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 340  01  Computer Architecture  M  W  F    1215  1320  OSS 429  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:1215  1320 Location:OSS 429 Course Registration Number:20667 (View in ClassFinder) Credit Hours:4 Instructor:Joseph M. Myre (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 419  01  Accounting Information Systems  M  W      1730  1915  OSS 431  
Description of course Genetics B/ Lab: 
Days of Week:M  W     Time of Day:1730  1915 Location:OSS 431 Course Registration Number:20624 (View in ClassFinder) Credit Hours:4 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  02  Accounting Information Systems   T  R     1525  1700  OSS 431  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:1525  1700 Location:OSS 431 Course Registration Number:20625 (View in ClassFinder) Credit Hours:4 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  03  Accounting Information Systems   T  R     1730  1915  OSS 431  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:1730  1915 Location:OSS 431 Course Registration Number:20689 (View in ClassFinder) Credit Hours:4 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 490  01  Topics: Algorithms  M  W  F    0935  1040  OSS 429  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:0935  1040 Location:OSS 429 Course Registration Number:21768 (View in ClassFinder) Credit Hours:4 Instructor:Sarah B. Miracle CISC 490 01, Topics: Algorithms (4 credits) Introduction to the design and analysis of algorithms. Course topics may include basic number theoretic algorithms, divide and conquer, graph algorithms, dynamic programming, and greedy algorithms. The course will also give an introduction to computational complexity, including NPcompleteness and the P versus NP problem. Prerequisites: MATH 128 and CISC 231 with a minimum grade of C Schedule Details


CISC 490  D02  Topics: Software Engineering  M  W      1525  1700  OSS 429  
Description of course Genetics B/ Lab: 
Days of Week:M  W     Time of Day:1525  1700 Location:OSS 429 Course Registration Number:22370 (View in ClassFinder) Credit Hours:4 Instructor:Jason E. Sawin The senior capstone course provides computer science majors the opportunity to integrate the knowledge that they have gained from across the curriculum. Students will work in groups to design, document and implement a large sized software project. During this process, students will be exposed to programming team organization, software development practices, as well as tools that facilitate the development of software systems. Prereqs: 1) Senior standing, and 2) a minimum grade of C in CISC 231 Schedule Details

Summer 2017 Courses
Course  Section  Title  Days  Time  Location  

CISC 130  01  IntroProgram&Prob SolvingSci   T W R F    1000  1300  OSS 431  
Description of course Genetics B/ Lab: 
Days of Week: T W R F   Time of Day:1000  1300 Location:OSS 431 Course Registration Number:30490 (View in ClassFinder) Credit Hours:4 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

Below are courses offered in Statistics. For uptodate information regarding course information for registration, please visit Murphy Online.
JTerm 2017 Courses
Course  Section  Title  Days  Time  Location  

STAT 201  01  Introductory Statistics II   T W R     1400  1600  OSS 429  
Description of course Genetics B/ Lab: 
Days of Week: T W R    Time of Day:1400  1600 Location:OSS 429 Course Registration Number:10078 (View in ClassFinder) Credit Hours:2 Instructor:Sergey S. Berg (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    1000  1300  OSS 429  
Description of course Genetics B/ Lab: 
Days of Week: T W R F   Time of Day:1000  1300 Location:OSS 429 Course Registration Number:10041 (View in ClassFinder) Credit Hours:4 Instructor:Sergey S. Berg 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    1215  1515  OSS 432  
Description of course Genetics B/ Lab: 
Days of Week: T W R F   Time of Day:1215  1515 Location:OSS 432 Course Registration Number:10042 (View in ClassFinder) Credit Hours:4 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

JTerm 2017 Courses
Course  Section  Title  Days  Time  Location 

Spring 2017 Courses
Course  Section  Title  Days  Time  Location  

STAT 220  01  Statistics I  M  W  F    0815  0920  OSS 431  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:0815  0920 Location:OSS 431 Course Registration Number:20774 (View in ClassFinder) Credit Hours:4 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  02  Statistics I  M  W  F    0815  0920  OSS 329  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:0815  0920 Location:OSS 329 Course Registration Number:20775 (View in ClassFinder) Credit Hours:4 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 431  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:0935  1040 Location:OSS 431 Course Registration Number:20776 (View in ClassFinder) Credit Hours:4 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: 
Days of Week:M  W  F   Time of Day:0935  1040 Location:OSS 329 Course Registration Number:20777 (View in ClassFinder) Credit Hours:4 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  OSS 329  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:1055  1200 Location:OSS 329 Course Registration Number:20778 (View in ClassFinder) Credit Hours:4 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      1335  1510  OSS 127  
Description of course Genetics B/ Lab: 
Days of Week:M  W     Time of Day:1335  1510 Location:OSS 127 Course Registration Number:20779 (View in ClassFinder) Credit Hours:4 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  07  Statistics I  M  W      1730  1915  OSS 432  
Description of course Genetics B/ Lab: 
Days of Week:M  W     Time of Day:1730  1915 Location:OSS 432 Course Registration Number:20780 (View in ClassFinder) Credit Hours:4 Instructor:Adam M. Johnson 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 329  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:0800  0940 Location:OSS 329 Course Registration Number:20782 (View in ClassFinder) Credit Hours:4 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     0955  1135  OSS 333  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:0955  1135 Location:OSS 333 Course Registration Number:20783 (View in ClassFinder) Credit Hours:4 Instructor:Sergey S. Berg 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 329  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:0955  1135 Location:OSS 329 Course Registration Number:20784 (View in ClassFinder) Credit Hours:4 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  12  Statistics I   T  R     1330  1510  OSS 329  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:1330  1510 Location:OSS 329 Course Registration Number:20785 (View in ClassFinder) Credit Hours:4 Instructor:Sergey S. Berg 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     1525  1700  OSS 333  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:1525  1700 Location:OSS 333 Course Registration Number:20786 (View in ClassFinder) Credit Hours:4 Instructor:Aran W. Glancy 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: 
Days of Week: T  R    Time of Day:1525  1700 Location:OSS 329 Course Registration Number:20787 (View in ClassFinder) Credit Hours:4 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   T  R     1330  1510  OSS 429  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:1330  1510 Location:OSS 429 Course Registration Number:21061 (View in ClassFinder) Credit Hours:4 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     0955  1135  OSS 214  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:0955  1135 Location:OSS 214 Course Registration Number:21223 (View in ClassFinder) Credit Hours:4 Instructor:Wenyuan Zheng 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  D01  Applied Statistical Methods   T  R     1330  1510  OSS 214  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:1330  1510 Location:OSS 214 Course Registration Number:20773 (View in ClassFinder) Credit Hours:4 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  D02  Applied Statistical Methods   T  R     1525  1700  OSS 214  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:1525  1700 Location:OSS 214 Course Registration Number:21247 (View in ClassFinder) Credit Hours:4 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 370  01  Bayesian Models  M  W      1525  1700  OSS 214  
Description of course Genetics B/ Lab: 
Days of Week:M  W     Time of Day:1525  1700 Location:OSS 214 Course Registration Number:21542 (View in ClassFinder) Credit Hours:4 Instructor:Arkady Shemyakin The course covers a range of statistical models used in applications including: Actuarial Science, Finance, Health and Social Sciences. It is oriented towards practical model construction and problem sovling. Review of parametric statistical models and principles of statistical inference. Application to loss and ruin models. Construction of empirical and parametric models and model selection. Credibility theory. Simulation. Offered every other year. Prerequisite: MATH 313 and STAT 314 or STAT 220 and STAT 320 Schedule Details

Spring 2017 Courses
Course  Section  Title  Days  Time  Location 

Summer 2017 Courses
Course  Section  Title  Days  Time  Location  

STAT 220  01  Statistics I  M T W R     1030  1230  OSS 432  
Description of course Genetics B/ Lab: 
Days of Week:M T W R    Time of Day:1030  1230 Location:OSS 432 Course Registration Number:30037 (View in ClassFinder) Credit Hours:4 Instructor:Sergey S. Berg 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 T W R     1715  1915  OSS 432  
Description of course Genetics B/ Lab: 
Days of Week:M T W R    Time of Day:1715  1915 Location:OSS 432 Course Registration Number:30038 (View in ClassFinder) Credit Hours:4 Instructor:James P. Normington 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

Summer 2017 Courses
Course  Section  Title  Days  Time  Location 
