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UID:20250714T104523EDT-0586RO4SmG@132.216.98.100
DTSTAMP:20250714T144523Z
DESCRIPTION:The Central Limit Theorem\, Testing for Normality\, and Other M
 isleading Ideas\n\nMany statistical concepts and practices are taught in a
  shallow or mechanistic way\, and the full ramifications of such approache
 s are not appreciated by instructors or students. A case in point is the c
 entral limit theorem\, which has been used to justify all kinds of statist
 ical approaches even when it doesn't actually work with the sample sizes s
 een in practice. And statisticians have thought too little about what 'wor
 k' means. There are hidden assumptions in the CLT that students often do n
 ot appreciate. This is related to the nonexistence of nonparametric confid
 ence intervals for population means. Another example is the common practic
 e of testing data for normality\, then choosing a parametric test vs. a no
 nparametric test. This practice involves multiple misunderstandings. The p
 ermutation t-test is another example that will be covered.\n
DTSTART:20180917T190000Z
DTEND:20180917T200000Z
LOCATION:Room 208/09 2nd floor\, McIntyre Medical Building\, CA\, QC\, Mont
 real\, H3G 1Y6\, 3655 promenade Sir William Osler
SUMMARY:Frank E. Harrell Jr\, Vanderbilt University - School of Medicine - 
 Nashville TN
URL:/mathstat/channels/event/frank-e-harrell-jr-vander
 bilt-university-school-medicine-nashville-tn-289632
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