Course Descriptions

An introduction to the language of statistics and some statistical methods, including random variables and their distribution; random sampling, normal distribution, estimation of parameters and testing hypotheses.

A calculus-based study of probability, discrete and continuous random variables, mathematical expectation, moment generating functions, Central Limit Theorem, sampling from normal populations, confidence intervals, hypothesis testing.

The ability to analyze data is an increasingly important skill in many fields of study. This problem-based course introduces common inferential statistics and data analysis techniques to students interested in improving critical thinking about data and evidence-based decision making. Students will explore different data visualization and data analysis techniques in the context of practical problems and students will investigate predictive analysis techniques using statistical software or spreadsheet add-ins.

This course introduces modern tools and techniques used for manipulation, analysis and visualization of data using software. Students will study regression models to make predictions and analyze the relationship between variables. Students will gain hands-on experience visualizing, analyzing, and interpreting data from multiple disciplines such as social sciences, life sciences, physical sciences, economics, education, and engineering.

This course gives a practical introduction to experimental designs. Students will design single-factor and factorial experiments. Students will analyze the effect of each factor as well as the interaction effect among factors. Commonly used statistical tests such as t-tests and ANOVAs will be used for analyzing the data. Students will gain hands-on experience applying statistical techniques to real-world data from multiple disciplines such as social sciences, life sciences, physical sciences, economics, education, and engineering.