Course Offerings
Below are courses offered in Computer and Information Sciences. For uptodate information regarding course information for registration, please visit Murphy Online.
Summer 2016 Courses
Course  Section  Title  Days  Time  Location  

CISC 130  01  IntroProgram&Prob SolvingSci  M T W R     0800  1100  OSS 431  
Description of course Genetics B/ Lab: 
Days of Week:M T W R    Time of Day:0800  1100 Location:OSS 431 Course Registration Number:30471 (View in ClassFinder) Credit Hours:4 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

Fall 2016 Courses
Course  Section  Title  Days  Time  Location  

CISC 130  01  IntroProgram&Prob SolvingSci  See Details  *  *  
Description of course Genetics B/ Lab: 
Days of Week:See Details Time of Day:* Location:* Course Registration Number:40685 (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 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:40875 (View in ClassFinder) Credit Hours:4 Instructor:Volker P. Petersen (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:40957 (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  See Details  *  *  
Description of course Genetics B/ Lab: 
Days of Week:See Details Time of Day:* Location:* Course Registration Number:41043 (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  07  IntroProgram&Prob SolvingSci  M  W      1730  2015  OSS 431  
Description of course Genetics B/ Lab: 
Days of Week:M  W     Time of Day:1730  2015 Location:OSS 431 Course Registration Number:41880 (View in ClassFinder) Credit Hours:4 Instructor:Andrew J. Bartczak (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:41368 (View in ClassFinder) Credit Hours:4 Instructor:Sarah B. Miracle 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:41743 (View in ClassFinder) Credit Hours:4 Instructor:Sarah B. Miracle 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    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:40687 (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  02  IntroComputer Tech & Bus Appl  M  W  F    1215  1320  OSS 432  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:1215  1320 Location:OSS 432 Course Registration Number:40688 (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  03  IntroComputer Tech & Bus Appl  M  W  F    1335  1440  OSS 431  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:1335  1440 Location:OSS 431 Course Registration Number:41369 (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  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:41881 (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  05  IntroComputer Tech & Bus Appl   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:41882 (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:42002 (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:40691 (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:43290 (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 333  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:1055  1200 Location:OSS 333 Course Registration Number:40689 (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 231  02  Data StructuresObject Design  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:43224 (View in ClassFinder) Credit Hours:4 Instructor:Scott C. Yilek (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 310  01  Operating Systems  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:40826 (View in ClassFinder) Credit Hours:4 Instructor:Paul Pederson (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  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:40701 (View in ClassFinder) Credit Hours:4 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 342  01  Computer AppExperimental Sci  M  W      1525  1700  OSS 415  
Description of course Genetics B/ Lab: 
Days of Week:M  W     Time of Day:1525  1700 Location:OSS 415 Course Registration Number:41883 (View in ClassFinder) Credit Hours:4 Instructor:Joseph M. Myre (Formerly QMCS 342) Introduction to the use of computers in the collection and analysis of scientific information. The course is designed to meet the needs of both natural science majors with an interest in scientific computing and computer science majors with an interest in laboratory science. Emphasis is placed on application of concepts and techniques in addition to LabVIEW programming. Topics include laboratory device interfacing, analogsignal acquisition and processing, frequency transformations, data analysis, image processing, and math modeling and simulation. Prerequisites: CISC 130 or 131; MATH 109 or 111 or 113; one course in a laboratory science Schedule Details


CISC 419  01  Accounting Information Systems   T  R     1525  1700  OSS 432  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:1525  1700 Location:OSS 432 Course Registration Number:40690 (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  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:41706 (View in ClassFinder) Credit Hours:4 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 450  01  Database Design I  M  W  F    0935  1040  OSS 333  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:0935  1040 Location:OSS 333 Course Registration Number:40827 (View in ClassFinder) Credit Hours:4 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


CISC 450  02  Database Design I  M  W  F    1055  1200  OSS 429  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:1055  1200 Location:OSS 429 Course Registration Number:43355 (View in ClassFinder) Credit Hours:4 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

JTerm 2017 Courses
Course  Section  Title  Days  Time  Location  

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

Below are courses offered in Statistics. For uptodate information regarding course information for registration, please visit Murphy Online.
Summer 2016 Courses
Course  Section  Title  Days  Time  Location  

STAT 220  01  Statistics I  M T W R     0815  1015  OSS 313  
Description of course Genetics B/ Lab: 
Days of Week:M T W R    Time of Day:0815  1015 Location:OSS 313 Course Registration Number:30046 (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


STAT 220  02  Statistics I  M T W R     1030  1230  OSS 313  
Description of course Genetics B/ Lab: 
Days of Week:M T W R    Time of Day:1030  1230 Location:OSS 313 Course Registration Number:30047 (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

Fall 2016 Courses
Course  Section  Title  Days  Time  Location  

STAT 220  01  Statistics I  M  W  F    0815  0920  OSS 328  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:0815  0920 Location:OSS 328 Course Registration Number:40943 (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 328  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:0935  1040 Location:OSS 328 Course Registration Number:40945 (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  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:40946 (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:40947 (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  F    1055  1200  OSS 432  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:1055  1200 Location:OSS 432 Course Registration Number:40948 (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  F    1215  1320  OSS 328  
Description of course Genetics B/ Lab: 
Days of Week:M  W  F   Time of Day:1215  1320 Location:OSS 328 Course Registration Number:40949 (View in ClassFinder) Credit Hours:4 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   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:40950 (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  09  Statistics I   T  R     0800  0940  OSS 431  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:0800  0940 Location:OSS 431 Course Registration Number:40951 (View in ClassFinder) 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  10  Statistics I   T  R     0955  1135  OSS 431  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:0955  1135 Location:OSS 431 Course Registration Number:40952 (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  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:40953 (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  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:40954 (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 220  13  Statistics I   T  R     1330  1510  OSS 432  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:1330  1510 Location:OSS 432 Course Registration Number:40955 (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  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:41160 (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  15  Statistics I   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:40956 (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 314  01  Mathematical Statistics   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:41002 (View in ClassFinder) Credit Hours:4 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 214  
Description of course Genetics B/ Lab: 
Days of Week: T  R    Time of Day:1525  1700 Location:OSS 214 Course Registration Number:41321 (View in ClassFinder) Credit Hours:4 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  D01  Statistics II   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:42711 (View in ClassFinder) Credit Hours:4 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

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:Staff (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 329  
Description of course Genetics B/ Lab: 
Days of Week: T W R F   Time of Day:1000  1300 Location:OSS 329 Course Registration Number:10041 (View in ClassFinder) Credit Hours:4 Instructor:Staff 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
