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MATH 341

Statistical Model Analysis

This course introduces students to elementary probability and data analysis via visual presentation of data, descriptive statistics and statistical inference. Emphasis will be placed on applications with examples drawn from a wide range of disciplines in both physical and behavioral sciences and humanities. Topics of statistical inference include: confidence intervals, hypothesis testing, regression, correlation, contingency tables, goodness of fit and ANOVA. The course will also develop familiarity with the most commonly encountered tables for probability distributions: binomial, normal, chi-squared, student-t and F. Pre-requisite: MATH 141 or ECON 350 or PSY 214 or BIO 275.

Distribution Area Prerequisites Credits
Science and Mathematics MATH 141 or ECON 350 or PSY 214 or BIO 275 1 course