Loading Events

« All Events

Visualizing Samples with Boxplots: Kick the Bar Chart Habit

February 27, 2025 at 2:00 pm - 3:00 pm

Free

This session will address the advantages of box plots over bar charts for displaying the spread and variability in data. Participants will learn how box plots can be used to compare multiple samples, the impact of sample size on data representation, and the efficient identification of outliers.

By the end of the session, participants should be able to create and interpret box plots, appreciate their usefulness in comparing multiple samples, understand the implications of sample size, and identify outliers and median confidence intervals through notches in box plots.

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.

Register for individual workshops

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.

 

Details

Date:
February 27, 2025
Time:
2:00 pm - 3:00 pm
Cost:
Free

Venue

Library Building (LIB)
3287 University Way
Kelowna, BC V1V 1V7 Canada
+ Google Map

Additional Info

Room Number
111
Registration/RSVP Required
Yes (see event description)
Event Type
Workshop/Course
Topic
Research and Innovation, Student Learning
Audiences
Students, Postdoctoral Fellows and Research Associates