Compare Dependency of Categorical Variables with Chi-Square Test (Stat-12)

Let’s make it a little bit easier with an example. Suppose you toss a coin 18 times. Generally, the probability of the outcome of head and tail is o.5. So, the probability says if you toss a coin 18 times, you should get 9 times head and 9 times tail. But you observed the occurrence of the head is 12 times instead of 9 times. That means there is a difference between the expected and the observed value. Chi-Square test shows how close our observed and expected value is! <h2>Chi-Square Test (X²)</h2> The Chi-Square test is a test that identifies whether there are any significant differences between the observed number of occurrences of an event and the expected number of occurrences or not. According to Wikipedia — <a href="https://towardsdatascience.com/compare-dependency-of-categorical-variables-with-chi-square-test-982baff64e81">Read More</a>