Statistical Fundamentals: A Visual Approach Workshop Series—Correlation, Causation and Association
March 28 at 2:00 pm - 3:00 pmFree
This session will address the concepts of correlation, causation, and association in data. Participants will learn to differentiate between these concepts and to recognize and interpret various types of correlations.
By the end of the session, participants should be able to distinguish between correlation and causation, recognize the impact of confounding variables on associations, evaluate correlation reliability, and understand the significance of correlation results.
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 can either register for the whole series, or register for individual workshops that are most applicable to you.