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DTSTART:20260115T210000Z
DTEND:20260115T220000Z
DTSTAMP:20260115T000000Z
SUMMARY:Statistical Fundamentals (1 of 8): Population Distributions\, Sampling Distributions\, and Central Limit Theorem
DESCRIPTION:\nStatistical Fundamentals: A Visual Approach Series\n\n\nThis 
 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.\n\n\nPopulation Distributions\, Sampling 
 Distributions\, and Central Limit Theorem (workshop 1 of 8): This session 
 will introduce participants to the foundational concepts of statistical 
 inference\, including population distributions\, sampling distribution\, 
 and the process of random sampling.\n\n\n\nBy the end of this 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.\n\n\nQuestions? Please 
 reach out to the Centre for Scholarly Communication at csc.ok@ubc.ca.\n\nA 
 full schedule of workshops can be found at csc.ok.ubc.ca/workshops/
LOCATION:LIB 111\, Okanagan - Centre for Scholarly Communication 
ORGANIZER;CN="Centre for Scholarly Communication (CSC)":MAILTO:csc.ok@ubc.ca
CATEGORIES:Data
CONTACT;CN="Centre for Scholarly Communication (CSC)":MAILTO:csc.ok@ubc.ca
STATUS:CONFIRMED
UID:LibCal-3973364
URL:https://libcal.library.ubc.ca/event/3973364
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