Statistical Fundamentals: A Visual Approach Workshop Series—ANOVA and Blocking

This session will introduce participants to the Analysis of Variance (ANOVA), a statistical method used for comparing the means of three or more groups. The concept of blocking will also be introduced to reduce noise and isolate sources of variation.

By the end of the session, participants should be able to use ANOVA for multi-treatment analysis, implement blocking in experimental design, calculate the F statistic for assessing significance, and appreciate how blocking can improve the efficiency of a study.

This workshop qualifies for the Scholarly Research, Writing, and Publishing Credential offered through the College of Graduate Studies.

Workshop Leader: Nijiati Abulizi, Centre for Scholarly Communication Data Consultant

Nijiati specializes in data wrangling and visualization and statistical analysis. He provides support with R (both base R and tidyverse), RStudio, R Markdown (including bookdown), Python and Jupyter Notebook, Git and GitHub, and QIIME.

Statistical Fundamentals: A Visual Approach Workshop Series

This series will use R and Python to help develop an intuition for fundamental statistical concepts using data visualization. These workshops are equally suitable to those hoping to enhance their ability to interpret common statistical tests and concepts as it is for those applying statistical modelling to their work. No background in statistics is required, but some familiarity with R or Python will be advantageous.

You may wish to review the asynchronous content of either R Fundamentals for Data Analysis or Python Basics for Data Analysis, or keep an eye out for the next time these workshops are offered.

You can either register for the whole series, or register for individual workshops that are most applicable to you.

Register Now