Statistical Fundamentals (2 of 8): Visualizing Errors and Common Pitfalls

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.

Visualizing Errors and Common Pitfalls (workshop 2 of 8): This session will address the visualization of standard deviation (s.d.), standard error of the mean (s.e.m.), and confidence interval (CI) error bars to build understanding of uncertainty in data analysis. The interpretation of error bars for statistical significance will be discussed, along with common pitfalls to avoid.

By the end of the session, participants should be able to visualize and interpret error bars, understand the implications of their spacing and width, and be cautious of common pitfalls such as misinterpreting non-overlapping error bars as evidence of significance.

REGISTER FOR INDIVIDUAL WORKSHOP

Register for all workshops in the series

For a complete list of upcoming CSC Workshops, please visit our workshops page.

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

Questions? Contact the Centre for Scholarly Communication at csc.ok@ubc.ca.