Bivariate Analysis for Categorical & Numerical | Statistics Tutorial #20 | MarinStatsLectures

Bivariate Analysis Categorical and Numerical Variables: Learn all about Bivariate Analysis when Y variable is numeric (or numerical, quantitative), and X variable is categorical (or qualitative) with examples.👍🏼Best Statistics & R Programming Language Tutorials: ( https://goo.gl/4vDQzT )

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▶︎ In this statistics tutorial, you will get an overview of bivariate analysis when Y variable (Dependent variable /outcome variable) is numeric (or numerical, quantitative), and X variable (independent variable/explanatory variable) is categorical (or qualitative). Specifically, this tutorial is an introduction to: paired t-test, 2-sample t-test, wilcoxon signed rank test, wilcoxon rank sum test aka mann whitney u test, one way analysis of variance, kruskal wallis one way analysis of variance, and multiple comparisons in the context of one way analysis of variance. We discuss the pros and cons of matching or pairing, as well as when it is and isn't possible.

▶︎This statistics tutorial is intended to set up all of what is covered in Module 5 as mentioned in the "course overview" (https://youtu.be/AN3UkzE3HMg)
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►Graphs and Descriptive Statistics in R using R Studio (Series 2): https://bit.ly/2PkTneg
►Probability distributions in R using R Studio (Series 3): https://bit.ly/2AT3wpI
►Bivariate analysis in R using R Studio (Series 4): https://bit.ly/2SXvcRi
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Видео Bivariate Analysis for Categorical & Numerical | Statistics Tutorial #20 | MarinStatsLectures канала MarinStatsLectures-R Programming & Statistics