What you will learn

Basics of statistical inference, confidence intervals and hypothesis testing. Commonly used tests. Pvalues, statistical and practical significance.
Analysis of Variance (ANOVA) and post-hoc tests. Diagnostics, implementation and interpretation using R.
Numerical Methods: The use of simulations, nonparametric bootstrap and permutation tests using R.
Linear Regression, Analysis of Variance with Covariates (ANCOVA), Generalised Linear Models (GLMs) and Mixed Effects Linear models using R.
Basics of power analysis (sample size evaluation) and some thoughts on experimental design.

Program Overview

Expert instruction

2 skill-building courses

Self-paced

Progress at your own speed

3 months

5 - 10 hours per week

$556.20

~~$618~~USD

For the full program experience

Courses in this program

Professor of Statistics

University of Canterbury

Experts from UCx committed to teaching online learning

$556.20

~~$618~~USD

2 courses in 3 months

I would like to receive email from UCx and learn about other offerings related to Statistical Analysis in R.

Drive your career forward with university-backed credit programs and verified certificates

Study and demonstrate knowledge on your schedule

Try a course before you pay

Learn with university partners and peers from around the world