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STAT 107 - Business Statistics |

An introduction to the discipline of statistics, emphasizing its applications in a business context. Topics include descriptive and inferential statistics, relevant probability distributions such as normal and binomial, regression, confidence intervals, and hypothesis testing. Appropriate statistical software such as Microsoft Excel or R is explored for both computation and presentation. Note: Students may not receive credit for both this course and STAA 127 Statistics for Social Sciences, STAT 117 Introduction to Statistics, STAT 157 Probability and Statistics, or STAT 203 Statistics for the Natural Sciences.
Prerequisite: Satisfactory mathematics placement.
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 107R - Business Statistics |

An introduction to the discipline of statistics, emphasizing its applications in a business context. Topics include descriptive and inferential statistics, relevant probability distributions such as normal and binomial, regression, confidence intervals, and hypothesis testing. Appropriate statistical software such as Microsoft Excel or R is explored for both computation and presentation. This course includes an additional one-hour per week lecture recitation. Topics may vary by section at the discretion of the instructor with the goal of supporting students' readiness for, and success, in the lecture course. Note: Students may not receive credit for both this course and STAA 127 Statistics for the Social Sciences, STAT 117 Introduction to Statistics, STAT 157 Probability and Statistics, or STAT 203 Statistics for the Natural Sciences.
1.000 Credit hours 4.000 Lecture hours 1.000 Other hours Levels: Undergraduate Schedule Types: Directed Study, Lecture Mathematics Department Course Attributes: D.v1_DomainGenEd-Domain II-A, D.v1_DomainGenEd-Core Math, Undergraduate Level Course, Lrng Objective 00, Lrng Objective 03, Lrng Objective 08, MATH Crs w/Recitation Req'd |

STAT 117 - Introduction to Statistics |

An introduction to the discipline of statistics, emphasizing both statistical thinking and analysis of real-world data. Topics include sampling, organizing and exploring data, probability distributions such as the normal distribution, sampling distributions, hypothesis testing and confidence intervals, and correlation and regression. Emphasis is placed on the analysis of collected data in order to apply an appropriate inferential test. Students are expected to express results of statistical procedures in ordinary non-technical language. Appropriate statistical software is explored. Note: Students may not receive credit for both this course and STAA 127 Statistics for Social Sciences, STAT 107 Business Statistics, STAT 157 Probability and Statistics, or STAT 203 Statistics for the Natural Sciences.
Prerequisite: Satisfactory mathematics placement.
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 117R - Introduction to Statistics |

An introduction to the discipline of statistics, emphasizing both statistical thinking and analysis of real-world data. Topics include sampling, organizing and exploring data, probability distributions such as the normal distribution, sampling distributions, hypothesis testing and confidence intervals, and correlation and regression. Emphasis is placed on the analysis of collected data in order to apply an appropriate inferential test. Appropriate statistical software is explored. This course includes an additional a one-hour per week lecture recitation. Topics may vary by section at the discretion of the instructor with the goal of supporting students' readiness for, and success, in the lecture course. Note: Students may not receive credit for both this course and STAA 127 Statistics for Social Sciences, STAT 107 Business Statistics, STAT 157 Probability and Statistics, or STAT 203 Statistics for the Natural Sciences.
1.000 Credit hours 4.000 Lecture hours 1.000 Other hours Levels: Undergraduate Schedule Types: Directed Study, Lecture Mathematics Department Course Attributes: D.v1_DomainGenEd-Domain II-A, D.v1_DomainGenEd-Core Math, Undergraduate Level Course, Lrng Objective 00, Lrng Objective 03, Lrng Objective 08, MATH Crs w/Recitation Req'd |

STAT 157 - Probability and Statistics |

A thorough introduction to probability and statistics. 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 STAA 127 Statistics for Social Sciences, STAT 107 Business Statistics or STAT 117 Introduction to Statistics or STAT 208 Statistics for the Natural Sciences.
Prerequisite: Eligibility to enroll in MATH 180 Precalculus.
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 203 - Statistics for the Natural Sciences |

A thorough introduction to the application of statistics to the sciences. Topics include a brief introduction to the appropriate descriptive statistics, relevant probability distributions, and a heavy focus on regression and hypothesis testing, including t-tests, chi-square tests for categorical data, and analysis of variance. Emphasis is placed on the analysis of data in order to apply an appropriate inferential test. Appropriate statistical software is employed. Note: Students may not receive credit for both this course and STAA 127 Statistics for the Social Sciences, STAT 107 Business Statistics, STAT 117 Introduction to Statistics, or STAT 157 Probability and Statistics.
Prerequisite: A grade of C (2.00) or higher in MATH 123 Introduction to Functions or the eligibility to enroll in MATH 180 Precalculus.
1.000 Credit hours 4.000 Lecture hours Levels: Non-Matriculated, Post-Baccalaureate Tchr Lcnse, Undergraduate Schedule Types: Directed Study, Lecture Mathematics Department Course Attributes: D.v1_DomainGenEd-Domain II-A, Undergraduate Level Course, Lrng Objective 00, Lrng Objective 03, Lrng Objective 07 |

STAT 307 - Intermediate Statistics |

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 |

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: Directed Study, Independent/Directed Study, Lecture Mathematics Department Course Attributes: Undergraduate Level Course |

STAT 341 - Mathematical Statistics I |

A rigorous study of sample spaces, events as subsets of a sample space, probability axioms, combinatorics applied to probability problems, random variables and their distributions, special distributions, multivariate distributions, central limit theorem, and topics in statistical inference. Note: Students cannot receive credit for both this course and MATH 348 Mathematical Statistics I.
Prerequisites: MATH 206 Discrete Mathematics I and MATH 221 Calculus III.
1.000 Credit hours 4.000 Lecture hours Levels: Non-Matriculated, Post-Baccalaureate Tchr Lcnse, Undergraduate Schedule Types: Directed Study, Lecture Mathematics Department Course Attributes: Undergraduate Level Course |

STAT 342 - Mathematical Statistics II |

A rigorous study of estimation, decision theory and hypotheses testing, linear models, regression, analysis of variance, analysis of categorical data, and nonparametric inference. Note: Students cannot receive credit for both this course and MATH 349 Mathematical Statistics II.
Prerequisite: STAT 341 Mathematical Statistics I.
1.000 Credit hours 4.000 Lecture hours Levels: Non-Matriculated, Post-Baccalaureate Tchr Lcnse, Undergraduate Schedule Types: Directed Study, Lecture Mathematics Department Course Attributes: Undergraduate Level Course |

STAT 807 - Intermediate Statistics |

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) |

STAT 841 - Mathematical Statistics I |

A rigorous study of sample spaces, events as subsets of a sample space, probability axioms, combinatorics applied to probability problems, random variables and their distributions, special distributions, multivariate distributions, central limit theorem, and topics in statistical inference. Note: Students cannot receive credit for both this course and MATH 848 Mathematical Statistics I.
1.000 Credit hours 4.000 Lecture hours Levels: Graduate, Non-Matriculated Schedule Types: Directed Study, Lecture Mathematics Department Course Attributes: Graduate Level Course |