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Statistical Fundamentals (7 of 8): ANOVA and Blocking
Statistical Fundamentals: A Visual Approach 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.
ANOVA and Blocking (workshop 7 of 8): 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.
Questions? Please reach out to the Centre for Scholarly Communication at csc.ok@ubc.ca.
A full schedule of workshops can be found at csc.ok.ubc.ca/workshops/