Correlation Analysis with R

R is one of the best or simply the best statistical programming language in the world.

This video lesson is all about CORRELATION ANALYSIS WITH R.
You'll learn a great deal of lesson and understand what it means to examine the relationship between variables.

The lesson covers in detail the following:
1. Pearson Product-Moment Correlation Coefficient
2. Spearman's Correlation Coefficient or Spearman's Rho (Non-parametric)
3. Kendall's tau Correlation Coefficient (Non-parametric)
4. Types of Correlation (Bivariate and Partial Correlation)
5. Biserial and Non-biserial correlation (Discrete and Continuous Dichotomous Variables)

THERE ARE GOING TO BE VERY POWERFUL PRESENTATIONS OF STATISTICAL INFERENCE IN R. THESE ARE THE TOPICS TO BE COVERED AND UPLOADED ON THE CHANNEL:
1. Statistical Inference with R - Concepts and Applications (COVERED)
2. Correlation Analysis (Pearson, SPearman, Kendall Tau, Point biserial, partial correlation, etc....) (COVERED)
3. Regression Analysis (Linear and Logistic Regression)
4. Comparing Two Means
5. Comparing Several Means (GLM1)
6. Analysis of Covariance (ANCOVA) (GLM2) and Factorial ANOVA (GLM3)
7. Repeated Measures Designs (GLM4) and Mixed Designs (GLM5)
8. Non-parametric Tests (Wilcoxon, Kruskal, Friedman's ANOVA, etc...)
9. Multivariate Analysis of Variance (MANOVA)
10. Exploratory Factor Analysis (PCA and Reliability Analysis)
11. Analyzing Categorical Data (Pearson Chi-Square, Fisher's Exact Test, etc...)
12. Multilevel Linear Models

DO YOU WANT TO BE A MASTER STATISTICIAN AND HAVE THESE IMPLEMENTED RIGHT IN R?

Then SUBSCRIBE TO THE CHANNEL FOR MORE OF THESE LESSONS!

[camillep]

Hello, thank you very much for the tutorial ! It is super helpful ! Would you know if there are any ways we can add the significance of the correlation based on the fdr correction and not on the raw p-value?
Thank you ! :)