Courses of Study

SC110s    Statistical Thinking Statistics is the science of learning from data; it provides tools for understanding data and arguments based on data in many diverse fields. Students will learn to describe data in basic terms and to verbalize interpretations of it. Topics include graphical and numerical methods for summarizing data, methods of data collection, basic study design, introductory probability, confidence intervals, and statistical inference. Does not count toward any major or minor. Credit may be received for only one of Mathematics or Statistics 110, 212, or 231. Four credit hours. Q. Viles
SC212fs    Introduction to Statistics and Data Science An exploration of statistical methods relevant to a broad array of scientific disciplines. Students will learn to properly collect data through sound experimental design and to present and interpret data in a meaningful way, making use of statistical computing packages. Topics include descriptive statistics, design of experiments, randomization, contingency tables, measures of association for categorical variables, confidence intervals, one- and two-sample tests of hypotheses for means and proportions, analysis of variance, correlation/regression, and nonparametrics. Credit can be received for only one of Mathematics or Statistics 110, 212, or 231. Four credit hours. Q, W2. O'Brien, Scott, Viles
[SC306]    Topics in Epidemiology The purposes of epidemiological research are to discover the causes of disease, to advance and evaluate methods of disease prevention, and to aid in planning and evaluating the effectiveness of public health programs. Students will learn about the historical development of epidemiology, a cornerstone of public health practice. Through the use of statistical methods and software, they will explore the analytic methods commonly used to investigate the occurrence of disease. Topics include descriptive and analytic epidemiology; measures of disease occurrence and association; observational and experimental study designs; and interaction, confounding, and bias. Prerequisite: Mathematics or Statistics 212, 231, or 382. Four credit hours.
SC308s    Topics in Psychometrics and Multivariate Statistics Psychometrics is concerned with the development and evaluation of psychological instruments such as tests and questionnaires. Students will learn about the fundamental concepts central to measurements derived from these tools. The establishment and assessment of the validity and reliability of research instruments, as well as the construction of scales and indices, will be discussed. Data reduction techniques and an introduction to testing theory will also be covered. Statistical software will be used throughout. Prerequisite: Statistics 212 and Mathematics 253 (may be taken concurrently). Four credit hours. O'Brien
SC321fs    Statistical Modeling Students will expand on their inferential statistical background and explore methods of modeling data through linear and nonlinear regression analysis. Through the use of statistical software, they will learn how to identify possible models based on data visualization techniques, to validate assumptions required by such models, and to describe their limitations. Topics include multiple linear regression, multicollinearity, logistic regression, models for analyzing temporal data, model-building strategies, transformations, model validation. Prerequisite: Mathematics or Statistics 212, 231, or 382. Four credit hours. Scott
SC381f    Mathematical Statistics I: Probability Listed as Mathematics 381. Four credit hours. O'Brien
SC382s    Mathematical Statistics II: Inference Building on their background in probability theory, students explore inferential methods in statistics and learn how to evaluate different estimation techniques and hypothesis-testing methods. Students learn techniques for modeling the response of a continuous random variable using information from several variables using regression modeling. Topics include method of moments and maximum likelihood estimation, sample properties of estimators including sufficiency, consistency, and relative efficiency, Rao-Blackwell theorem, tests of hypotheses, confidence intervals, linear models, and analysis of variance. Although applications are discussed, the emphasis is on theory. Prerequisite: Mathematics 381. Mathematics 253 and 274 are recommended. Four credit hours. O'Brien