Same as SDS 220. An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basis requirement for biological science, engineering, environmental science, neuroscience and psychology.

Same as MTH 220. (Formerly MTH 245). An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data.

(Formerly MTH/PSY 201 and MTH/PSY 190). An overview of the statistical methods needed for undergraduate research emphasizing methods for data collection, data description and statistical inference including an introduction to study design, confidence intervals, testing hypotheses, analysis of variance and regression analysis. Techniques for analyzing both quantitative and categorical data are discussed. Applications are emphasized, and students use R for data analysis. Classes meet for lecture/discussion and a required laboratory that emphasizes the analysis of real data.

An introduction to data science using Python, R and SQL. Students learn how to scrape, process and clean data from the web; manipulate data in a variety of formats; contextualize variation in data; construct point and interval estimates using resampling techniques; visualize multidimensional data; design accurate, clear and appropriate data graphics; create data maps and perform basic spatial analysis; and query large relational databases. No prerequisites, but a willingness to write code is necessary. (E)

Sectioned course.: Students are introduced to the basic strokes of tennis (forehand, backhand, volleys, serves). Singles and doubles play and basic positioning are presented. Tennis rules and etiquette are included in the curriculum. Enrollment limited to 16 per section.

An advanced perspective of the development of athletes’ functionality, strength and movement mechanics to improve overall performance. This course reviews lifting techniques, speed mechanics, functional training and practical theory of the athletic performance model and prepare students for applications of these principles in everyday sport coaching and to prepare for the NSCA-CSCS certification exam.

This course provides the opportunity to explore the dynamic world of sports leadership through a national and international lens. Students are exposed to alternative perspectives of leadership including some contemporary collaborative models. Students build a personal model and philosophy of leadership that they can put to immediate use in their coaching. (E)

A course in the application of biomechanics to exercise and sport. Information on linear and angular kinematics, linear and angular kinetics, and fluid mechanics is presented in order for students to analyze exercise and sport.

The administration of sport and athletic teams is the major focus of this course. Topics include planning, organizing, directing and controlling various facets including scheduling, purchasing, budgeting and recruiting of a sports program. Limited to those enrolled in ESS 505 and 506.

Topics course.: A seminar focusing on the relationship between physical activity and health.  Physical activity can be used as a strategy to prevent and treat chronic disease.  In this seminar, we will explore the evidence underlying the relationship between physical activity and health in a variety of populations. Major topics include physical activity and sedentary behavior epidemiology, measurement and study design, chronic disease etiology, and health disparities.  Emphasis is placed on critical evaluation of seminal and current research in the field. Enrollment limit of 14.