This course will present statistical methods and inference procedures with an emphasis on applications, computer implementation, and interpretation of results. Familiarity with the R programming language is highly recommended. Topics include simple and multiple regression, model selection, correlation, moderation/interaction analysis, logistic regression, the chi-square test, the Kruskal-Wallis test, analysis of variance (ANOVA), multivariate analysis of variance (MANOVA), factor analysis, and canonical correlation analysis.
- Examine and summarize data numerically and graphically.
- Given a data set and a question, choose the appropriate statistical procedure.
- Verify conditions for statistical procedures.
- Perform hypothesis tests and compute confidence intervals.
- Explore and model relationships among variables and use models to make predictions.
- Use software package R to implement statistical analyses.
- Interpret and critically evaluate statistical information and data-based arguments.
- Effectively communicate the results of statistical analysis.
- Use R Markdown to produce statistical reports and support reproducible research.
Return to the Courses page.
Call 1-877-895-3276 or send an email to email@example.com. Our enrollment advisers are available Monday through Friday, 8:30 a.m. to 5:00 p.m. CT.