T-Tests - Data Science Mock Interview (with FAANG Data Scientist)

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In this video, a senior FAANG data scientist, discusses the assumptions made when using T-Tests and their implications for real-world problems. Learn about the importance of independence, normality, and homogeneity of variance in data analysis, and discover alternative tests for scenarios where these assumptions are violated.

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Chapters (Powered by ChapterMe) -
00:00 - Intro
00:47 - T-tests popular assumptions and real-world problems
01:17 - Two t-test assumptions independence and normality
02:22 - T-test assumptions often violated
04:19 - Data analysis technique, error estimates, and methodology

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