Stats For Data Science - Tutorial 19- Type 1 And Type 2 Error In Statistics-Krish Naik Hindi

In statistics, a Type I error is a false positive conclusion, while a Type II error is a false negative conclusion. Making a statistical decision always involves uncertainties, so the risks of making these errors are unavoidable in hypothesis testing. The probability of making a Type I error is the significance level, or alpha (α), while the probability of making a Type II error is beta (β). These risks can be minimized through careful planning in your study design. ------------------------------------------------------------------------ All Playlist links are given below NLP Playlist: https://www.youtube.com/playlist?list=PLTDARY42LDV67aWThoZxflLYGnD3Rh3VG ML playlist in hindi: https://bit.ly/3NaEjJX Stats Playlist In Hindi:https://bit.ly/3tw6k7d Python Playlist In Hindi:https://bit.ly/3azScTI --------------------------------------------------------------------------------------------------------------- Please donate if you want to support the channel through GPay UPID, Gpay: krishnaik06@okicici Telegram link: https://t.me/joinchat/N77M7xRvYUd403DgfE4TWw ------------------------------------------------------------------------------------------------------------- Please join as a member in my channel to get additional benefits like materials in Data Science, live streaming for Members and many more https://www.youtube.com/channel/UCNU_lfiiWBdtULKOw6X0Dig/join ----------------------------------------------------------------------------------------------------------- Please do subscribe my other channel too https://www.youtube.com/channel/UCjWY5hREA6FFYrthD0rZNIw --------------------------------------------------------------------------------------------------------- Connect with me here: Twitter: https://twitter.com/Krishnaik06 Facebook: https://www.facebook.com/krishnaik06 instagram: https://www.instagram.com/krishnaik06