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If there is no relationship between the placement rate and the C.G.P.A., then the placed students should be equally spread across the different C.G.P.A. He records how many students who got placed fell into each of the following C.G.P.A. He obtains the placement records of the past five years from the placement cell database (at random). Let’s learn the use of chi-square with an intuitive example.Ī research scholar is interested in the relationship between the placement of students in the statistics department of a reputed University and their C.G.P.A (their final assessment score). What is a Chi-Square Test and Why Do We use it?Ī Chi-Square test is a test of statistical significance for categorical variables. When the data we want to analyze contains this type of variable, we turn to the chi-square test, denoted by χ², to test our hypothesis. For example, Customer Satisfaction (Excellent, Very Good, Good, Average, Bad), and so on

Ordinal Variable: A variable for which the categories can be placed in an order.For example, Marital Status (Single, Married, Divorcee) Gender (Male, Female, Transgender), etc. Nominal Variable: A nominal variable has no natural ordering to its categories.There are broadly two types of categorical variables: These variables are also called qualitative variables as they depict the quality or characteristics of that particular variable.įor example, the category “Movie Genre” in a list of movies could contain the categorical variables – “Action”, “Fantasy”, “Comedy”, “Romance”, etc. These categories are generally names or labels. They can be tricky to deal with in the data science world so let’s first define them.Ĭategorical variables fall into a particular category of those variables that can be divided into finite categories. I’m sure you’ve encountered categorial variables before, even if you might not have intuitively recognized them. Chi-Square Test of Association between Two Variables.Types of Chi-Square Tests (With implementation in R).What is a Chi-Square Test and Why Do We Use It?.Comprehensive & Practical Guide to Inferential Statistics.If you are new statistics and data science, I would recommend the below resources to get a comprehensive overview of the two broad topics: So let’s dive into the article to understand all about the chi-square test, what it is, how it works and how we can implement it in R. I’ve found the chi-square test to be quite helpful in my own projects. But the situation becomes tricky when working with categorical features (as most data scientists will attest to!). We can always opt for z-tests, t-tests or ANOVA when we’re dealing with continuous variables. One of the best ways to deal with this is by using the Chi-Square test. So, how will you check the statistical significance between the observed and the expected footfall values? Remember this is a categorical variable – ‘Days of the week’ – with 5 categories. Sounds like a prime statistics problem? That’s the idea! At the end of the week, you observe that the expected footfall was different from the actual footfall. Let’s say you can predict a certain number of people arriving for lunch five days a week. I want you to think of your favorite restaurant right now. “Science is advanced by proposing and testing a hypothesis, not by declaring questions unsolvable” – Nick Matzke We will also implement a chi-square test in R in this article.Learn about the different types of Chi-Square tests and where and when you should apply them.What is the chi-square test? How does it work?.