Portage Learning

This graduate course provides an introduction to descriptive and inferential statistics. The course is designed to help students gain an understanding of several different types of statistical approaches and skills in being able to discern the most appropriate statistical test to run on a given dataset. Students will also have the opportunity to directly apply the knowledge of these statistical procedures through statistical software in the applied projects component of the course. Topics include descriptive and inferential statistics, hypothesis testing, z-scores, t tests, ANOVA, correlational analysis, linear regression, and chi-square analysis.

CREDITS: 3

Prerequisites: MATH 110: Introduction to Statistics or equivalent

Course Registration

Course Topics

Module 1: Descriptive and inferential statistics, quantitative and qualitative data, variables, scales of measurement

Module 2: Graphing, frequency distributions, measures of central tendency, variability

Module 3: Sampling, probability, and hypothesis testing

Module 4: Z-scores, confidence intervals, effect size, and statistical power

Module 5: One sample t-test, paired samples t-test, independent samples t-test

Module 6: One-way and two-way ANOVA

Module 7: Pearson’s correlation, linear regression, multiple regression

Module 8: Non-parametric tests, Chi-square analysis