Association of Categorical Variables | Cramer's V

📺 In this video, we'll focus on categorical data analysis and introduce you to Cramer's V, which is often considered as the equivalent of Pearson's correlation for two categorical variables. 📊 🔍 If you haven't watched our previous tutorial on the chi-square contingency test, make sure to check it out first, as we'll be referencing it in this video to compute the chi-square value needed for Cramer's V calculation. Chi-square Test - https://youtu.be/-umkwnwDWJY 📝 Cramer's V is a measure of association between two categorical variables, ranging from 0 to 1. A value closer to 0 indicates a weak association, while a value closer to 1 indicates a strong association. It helps us understand the strength of the relationship between the variables. 💡 The formula for Cramer's V involves the chi-square value and the sample size. Once we have the chi-square value from the chi-square test, we can easily compute Cramer's V using the formula. 🔗 We'll show you step-by-step how to calculate Cramer's V for a given dataset and interpret the value to determine the strength of association between the categorical variables. 🔮 Stay tuned for more exciting tutorials on data analysis and statistics! Don't forget to like, share, and subscribe for more content. Happy analyzing! 🚀