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.
|Science and Mathematics||MATH 141 or ECON 350 or PSY 214 or BIO 275||1 course|