Summary
In this chapter, you discovered several methods for calculating the correlation coefficient for different types of variables in your data analysis. First, you learned how to calculate the correlation coefficient using the Pearson, Spearman, and Kendall methods for two numeric variables. These methods help you understand the strength and direction of the relationship between two numeric variables. You also explored how to calculate the correlation coefficient for two categorical variables using Cramér’s V and Theil’s coefficient of uncertainty. Finally, you learned how to calculate the correlation coefficient between a numeric variable and a categorical variable using the correlation ratio.
In the next chapter, you will see how statistics are really important for identifying outliers and imputing missing values in your dataset.
