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Mastering Kendall's Tau Rank Correlation Analysis in R

The Kendall's tau rank correlation coefficient can be easily calculated in R using the cor.test()-function. In addition the argument method="kendall" is required within cor.test(). ➡️ Watch next:    • p value calculation for Kendall tau c...   Please keep in mind that the calculation is for Kendall's tau b by default, which occupies the major part of this video. The calculation of Kendall's tau c will also be shown with the help of the DescTools-package. Furthermore I will elaborate on classifying the magnitude of your correlation aka. effect. For the latter I will also refer to Cohen (1992): A Power Primer and the thresholds provided, mainly applicable for the behavioral sciences. 📚 Literature =========== 📚 Cohen, J. (1992): Quantitative methods in psychology: A power primer. Psychological bulletin, pp. 155-159. ⏰ Timestamps: ============== 0:00 Introduction and three variations of Kendall's tau 0:28 Calculating Kendall's tau b using cor.test() in R 0:54 One-sided vs. two-sided testing 1:47 Interpretation: I) p value 2:19 Interpretation: II) correlation coefficient r 2:41 Interpretation: III) effect size classification 3:09 Calculating Kendall's tau c If you have any questions or suggestions regarding the Kendall Tau rank correlation in R, please use the comment function. Thumbs up or down to decide if you found the video helpful. #useR #statorials Support channel? 🙌🏼 =================== Paypal donation: https://www.paypal.com/paypalme/Bjoer... Amazon affiliate link: https://amzn.to/49BqP5H Thank you for your support! ♥