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Statistical Fundamentals: A Visual Approach Workshop Series—Population, Sampling, Sampling Distribution and Central Limit Theorem
February 1 at 2:00 pm - 3:00 pmFree
This session will introduce participants to the foundational concepts of statistical inference, including population distributions and the process of random sampling. Attendees will learn how sampling distributions evolve towards normality as sample sizes increase and will visually explore the Central Limit Theorem.
By the end of the session, participants should be able to visualize and understand population distributions, illustrate random sampling processes, recognize the normalizing effect of larger samples on sampling distributions, and demonstrate the Central Limit Theorem visually.
This workshop qualifies for the Scholarly Research, Writing, and Publishing Credential offered through the College of Graduate Studies.
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.