Catalog Entries |
Fall 2020
May 11, 2024 |
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 | Select the Course Number to get further detail on the course. Select the desired Schedule Type to find available classes for the course. |
| STAT 107 - Business Statistics |
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An introduction to the discipline of statistics, emphasizing its applications in a business context. Topics include descriptive and inferential statistics, probability, regression, confidence intervals, and hypothesis testing. Note: Students may not receive credit for both this course and either MATH 117 Introduction to Statistics or MATH 208 Biostatistics.
Prerequisite: Satisfactory score on the mathematics placement examination.
1.000 Credit hours 4.000 Lecture hours Levels: Non-Matriculated, Undergraduate Schedule Types: Independent/Directed Study, Lecture Mathematics Department Course Attributes: D.v1_DomainGenEd-Domain II-A, D.v1_DomainGenEd-Core Math, Undergraduate Level Course, Lrng Objective 03, Lrng Objective 08 |
| STAT 117 - Introduction to Statistics |
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An introduction to the discipline of statistics, emphasizing both statistical thinking and its application to analyzing data. Topics include sampling, design of experiments, organizing and exploring data, probability distributions such as the normal distribution, sampling distributions, hypothesis testing and confidence intervals, correlation and regression. Students are expected to express results of statistical procedures in ordinary non-technical language. Real world applications of statistical topics are emphasized throughout the course. Note: Students may not receive credit for both this course and MATH 107 Business Statistics or MATH 157 Probability and Statistics or MATH 208 Biostatistics.
Prerequisite: Satisfactory score on the mathematics placement examination.
1.000 Credit hours 4.000 Lecture hours Levels: Graduate, Non-Matriculated, Post-Baccalaureate Tchr Lcnse, Undergraduate Schedule Types: Independent/Directed Study, Lecture Mathematics Department Course Attributes: D.v1_DomainGenEd-Domain II-A, D.v1_DomainGenEd-Core Math, Undergraduate Level Course, Lrng Objective 03, Lrng Objective 08 |
| STAT 157 - Probability and Statistics |
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A study of probability and statistics intended for mathematics majors. After a brief survey of descriptive statistics, topics include counting techniques, discrete and continuous probability distributions, Bayes' rule, correlation and regression, confidence intervals, sampling distributions, the Central Limit Theorem, and hypothesis testing. Note: Students may not receive credit for both this course and MATH 107 Business Statistics or MATH 117 Introduction to Statistics or MATH 208 Biostatistics.
Prerequisite: Minimum score of 4.0 on the mathematics placement examination.
1.000 Credit hours 4.000 Lecture hours Levels: Graduate, Non-Matriculated, Post-Baccalaureate Tchr Lcnse, Undergraduate Schedule Types: Independent/Directed Study, Lecture Mathematics Department Course Attributes: D.v1_DomainGenEd-Domain II-A, D.v1_DomainGenEd-Core Math, Undergraduate Level Course, Lrng Objective 03, Lrng Objective 08 |
| STAT 208 - Biostatistics |
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A course that covers statistical methods as they apply to the biological, health, and food sciences. The major emphasis is on hypothesis testing, including regression and analysis of variance. Descriptive statistics is also included. The statistical package Minitab is used. Note: Students may not receive credit for both this course and MATH 107 Business Statistics or MATH 117 Introduction to Statistics or MATH 157 Probability and Statistics.
Prerequisite: A grade of C (2.00) or higher in MATH 123 College Algebra or the eligibility to enroll in MATH 180 Precalculus.
1.000 Credit hours 4.000 Lecture hours Levels: Graduate, Non-Matriculated, Undergraduate Schedule Types: Independent/Directed Study, Lecture Mathematics Department Course Attributes: Undergraduate Level Course |
| STAT 307 - Intermediate Statistics |
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A study of regression and correlation analysis, chi square tests and contingency tables, design of experiments, analysis of variance, non-parametric statistics, and introduction to data analysis.
Prerequisite: One (1) of the following: ENVS 202 Data Analysis for Scientists, QUAN 202 Statistical Analysis for Business and Economics, STAT 107 Business Statistics, STAT 117 Introduction to Statistics, STAT 157 Probability and Statistics, STAT 208 Biostatistics.
1.000 Credit hours 4.000 Lecture hours Levels: Non-Matriculated, Undergraduate Schedule Types: Directed Study, Lecture Mathematics Department Course Attributes: Undergraduate Level Course |
| STAT 308 - Applied Statistical Data Processing |
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Practical aspects of data analysis using statistical computer packages such as MINITAB, SPSSX, AND BMDP. Multivariate statistical methods including multiple regression, analysis of covariance, factor analysis, multidimensional scaling, discriminant analysis and linear models for cross-classified categorical data are emphasized. Students do individual data analysis projects.
Prerequisite: STAT 307 Intermediate Statistics.
1.000 Credit hours 4.000 Lecture hours Levels: Non-Matriculated, Undergraduate Schedule Types: Independent/Directed Study, Lecture Mathematics Department Course Attributes: Undergraduate Level Course |
| STAT 807 - Intermediate Statistics |
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A study of regression and correlation analysis, chi square tests and contingency tables, design of experiments, analysis of variance, non-parametric statistics, and introduction to data analysis.
1.000 Credit hours 4.000 Lecture hours Levels: Graduate, Non-Matriculated, Post-Baccalaureate Tchr Lcnse Schedule Types: Directed Study, Lecture Mathematics Department Course Attributes: Graduate Level Course, Graduate Level Course, Mathematics (MEd) |
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