3 credits
Fall 2026 Lecture Distance Learning Upper Division
Descriptive statistics; elementary probability; sampling distributions; inference, testing hypotheses, and estimation; normal, binomial, Poisson, hypergeometric distributions; one-way analysis of variance; contingency tables; regression. For statistics majors and minors, credit should be allowed in no more than one of STAT 30100, STAT 30301, STAT 35000, STAT 35500, STAT 50100, and in no more than one of STAT 50300 and STAT 51100. Prerequisite: Two semesters of college calculus.
Learning Outcomes1Understand the difference between population parameters and sample statistics.
2Understand practical data displays: meaning and interpretation of common data displays in the media.
3Appreciate various interpretations of probability and where they enter into statistical studies.
4Understand statistical distributions: difference between discrete and continuous random variables. Computing the mean and variance using various important probability distributions such as the Binomial, Hypergeometric, Poisson, Normal, Exponential, Gamma. Computing probabilities using these distributions.
5Understand statistical distributions of two or more random variables: Sample statistics and their distributions. Understanding the Central Limit Theorem.
6Understand statistical inference: to understand what this means and what are some practical and important applications. Examples include Confidence Intervals, Tests of Hypotheses for one, two or more populations. Linear Regression with emphasis on the difference between causation and relationships.
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