0 or 3 credits
Spring 2026 Lecture Distance Learning Upper Division
An introduction to methodologies for data analysis and simulation. Populations and sampling. Distributions and summaries of distributions. Algorithms for sampling and resampling. Foundational statistical concepts including confidence intervals, hypothesis testing, correlation. Introduction to classification and regression. Essential use is made of statistical software throughout. For statistics majors and minors, credit should be allowed in no more than one of STAT 30100, 30301, 35000, 35500, 50100, and in no more than one of STAT 50300 and STAT 51100.
Learning Outcomes1Utilize simulations to generate data (statistical simulations).
2Explain sampling distributions, their properties, and methods for resampling (Statistical Reasoning).
3Explain foundational concepts such as confidence intervals, hypothesis testing, correlations, etc., and apply these concepts in statistical process (Statistical Concepts).
4Assess statistical problems, and justify and apply statistical methods used to solve the problem (Statistical Thinking).
Prerequisites
Restrictions
made by Purdue students.