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Undergraduate Bulletin College of Arts and Sciences

Course descriptions, prerequisites and more...

Below you will find the list of courses offered through the College's schools, departments, and programs. This list includes important information about each course, including the course description, credit hours, prerequisites, repeatability, and more. Use the filters to narrow your search.

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30 courses found. Showing results 1–10.
  • STAT-H 100 Statistical Literacy, Honors (3 cr.) P: Consent of Hutton Honors College. R: Mastery of high school algebra; or MATH-M 014. How to be an informed consumer of statistical analysis. Experiments and observational studies, summarizing and displaying data, relationships between variables, quantifying uncertainty, drawing statistical inferences. Credit given for only one of STAT-H 100 or STAT-S 100.
  • STAT-K 310 Statistical Techniques (3 cr.) P: MATH-M 119 or equivalent. Introduction to probability and statistics. Elementary probability theory, conditional probability, independence, random variables, discrete and continuous probability distributions, measures of central tendency and dispersion. Concepts of statistical inference and decision: estimation, hypothesis testing, Bayesian inference, statistical decision theory. Special topics discussed may include regression and correlation, time series, analysis of variance, nonparametric methods. Credit given for only one of ANTH-A 306, CJUS-K 300, ECON-E 370, ECON-S 370, MATH-K 300, MATH-K 310, POLS-Y 395, PSY-K 300, PSY-K 310, SOC-S 371, SPEA-K 300, SPH-Q 381, STAT-K 310, STAT-S 300, STAT-S 301, or STAT-S 303.
  • STAT-S 100 Statistical Literacy (3 cr.) R: Mastery of high school algebra; or MATH-M 014. How to be an informed consumer of statistical analysis. Experiments and observational studies, summarizing and displaying data, relationships between variables, quantifying uncertainty, drawing statistical inferences. Credit given for only one of STAT-H 100 or STAT-S 100.
  • STAT-S 201 Networks 2.0: Quantitative Literacy (3 cr.) P: STAT-S 100 or STAT-H 100; or consent of instructor. How to understand, analyze, and view networks. Topics include network visualization, data gathering, and an overview of network theory and analysis. Students learn basic network terminology and see examples of network methodology, studying a wide variety of network structural analyses designed to illustrate network theories. Possible applications to social and behavioral sciences, information science, political science, public health, and Facebook.
  • STAT-S 211 Statistics for Journalists (3 cr.) R: Mastery of high school algebra; or MATH-M 014. Essential statistical concepts and tools for journalists in the age of data, including probability, graphics, descriptive statistics, prediction, study design, comparison, testing, and estimation. The course has a heavier emphasis on writing and reading media reports than other introductory statistics courses.
  • STAT-S 300 Introduction to Applied Statistical Methods (4 cr.) R: Mastery of high school algebra; or MATH-M 014. Lecture and laboratory. Introduction to methods for analyzing quantitative data. Graphical and numerical descriptions of data, probability models of data, inference about populations from random samples. Regression and analysis of variance. Credit given for only one of ANTH-A 306, CJUS-K 300, ECON-E 370, ECON-S 370, MATH-K 300, MATH-K 310, POLS-Y 395, PSY-K 300, PSY-K 310, SOC-S 371, SPEA-K 300, SPH-Q 381, STAT-K 310, STAT-S 300, STAT-S 301, or STAT-S 303.
  • STAT-S 301 Applied Statistical Methods for Business (3 cr.) P: Math-M 118 or equivalent. Introduction to methods for analyzing data arising in business, designed to prepare business students for the Kelley School's Integrative Core. Graphical and numerical descriptions of data, probability models, fundamental principles of estimation and hypothesis testing, applications to linear regression and quality control. Microsoft Excel used to perform analyses. Credit given for only one of ANTH-A 306, CJUS-K 300, ECON-E 370, ECON-S 370, MATH-K 300, MATH-K 310, POLS-Y 395, PSY-K 300, PSY-K 310, SOC-S 371, SPEA-K 300, SPH-Q 381, STAT-K 310, STAT-S 300, STAT-S 301, or STAT-S 303.
  • STAT-S 303 Applied Statistical Methods for the Life Sciences (3 cr.) R: Mastery of high school algebra; or MATH-M 014. Introduction to methods for analyzing data arising in the life sciences, designed for biology, human biology, and pre-medical students. Graphical and numerical descriptions of data, probability models, fundamental principles of estimation and hypothesis testing, inferences about means, correlation, linear regression. Credit given for only one of ANTH-A 306, CJUS-K 300, ECON-E 370, ECON-S 370, MATH-K 300, MATH-K 310, POLS-Y 395, PSY-K 300, PSY-K 310, SOC-S 371, SPEA-K 300, SPH-Q 381, STAT-K 310, STAT-S 300, STAT-S 301, or STAT-S 303.
  • STAT-S 320 Introduction to Statistics (3 cr.) P: MATH-M 212, MATH-S 212, MATH-M 301, MATH-M 303, or MATH-S 303. Basic concepts of data analysis and statistical inference, applied to 1-sample and 2-sample location problems, the analysis of variance, and linear regression. Probability models and statistical methods applied to practical situations using actual data sets from various disciplines. Credit given for only one of STAT-S 320 or STAT-S 350.
  • STAT-S 350 Introduction to Statistical Inference (3 cr.) P: One of the following: (1) (MATH-M 118, MATH-A 118, MATH-S 118, MATH-V 118, or [MATH-D 116 and MATH-D 117]) and (MATH-M 119, MATH-J 113, or MATH-V 119) and (STAT-H 100, STAT-K 310, STAT-S 100, STAT-S 211, STAT-S 300, STAT-S 301, STAT-S 303, ANTH-A 306, CJUS-K 300, ECON-E 370, ECON-S 370, MATH-E 265, MATH-M 365, POLS-Y 395, PSY-K 300, PSY-K 310, SOC-S 371, SPEA-K 300, or SPH-Q 381); (2) or (MATH-M 119 and MATH-X 201); (3) or MATH-M 211; or (4) (MATH-M 212 or MATH-S 212); (5) or consent of instructor. Explores the formulation of statistical inference using probability models. Addresses point estimation, hypothesis testing, and set estimation for various models, including 1-, 2-, and K-sample location problems, goodness-of-fit, correlation and regression. Credit given for only one of STAT-S 320 or STAT-S 350.