Imagine having a couple of categorical data sets that you need to compare.
These sets are completely different in nature, but understanding the correlation between them will help you draw important conclusions about your audience and make important business decisions based on them.
Researchers often use the Chi-Square Test to find correlations exactly in these types of scenarios.
In this article, we will tell you all about what the Chi-Square Test is, in which situations researchers use this approach, and what the exact steps and formulas are to successfully perform this type of test.
What Is the Chi-Square Test?
Simply put, the Chi-Square Test is a method used in statistics to determine if two certain categorical variables are somehow connected to each other.
What are the categorical variables, you ask? Well, it could be any grouping that has different characteristics (as variables) – like the types of online movie streaming services, with its variables such as Netflix, Disney+, Amazon Prime, and others.
Another example of categorical variables could be famous online publications with variables like Financial Times, Forbes, Business Insider, etc., or the age group in certain locations that are subscribed to online publications, like 18-25, 26-32, 33-40, etc.
In any case, whenever you have two different categorical variables and you want to determine whether there is any kind of correlation between those two, you can use the Chi-Square Test. For example, you could test if there is any connection between the age groups in certain locations and their preferred online publication to get news from.
This data can help you make essential strategic decisions that will help your campaigns be more accurate and get the desired results for your business growth.
When to Use the Chi-Square Test?
When it comes to conducting thorough market research, using the Chi-Square Test approach proves to be extremely useful.
However, it is important to keep in mind that you can’t use the Chi-Square Test if your variables are quantitative. At the same time, the sample you take for this type of test must be randomly selected from the whole amount of category of grouping you’d like to test against.
Moreover, it is recommended that the minimum number of observations of each combination of categorical variables must be five to ensure the accuracy and correctness of your research.
Types of Chi-Square Tests
There are two main types of Chi-Square Tests – both of them are used in different cases, and you must choose one according to your business needs and research objectives. Let’s have a close look at each one of them:
Goodness of Fit Test
Researchers use the Goodness of Fit type of Chi-Square Test when they have only one categorical variable to work with.
The idea is to learn about the ideal frequency of distribution for this particular categorical variable and see if your findings match your expectations. Oftentimes, default expectations claim that the proportions will be divided equally among categories.
Test of Independence
As the name suggests, researchers use the test of independence approach when they want to determine if categorical variables are different from one another.
Therefore, it should include two variables, and you must conduct a couple of different tests to determine their relationship. This is because conducting only one test might show results that are unusual and inaccurate when drawing conclusions.
How to Perform a Chi-Square Test?
Before we get into the steps for performing a Chi-Square Test, let’s take a look at the core formula that is used for this method.
The formula looks like this:
- Χ² is a Chi-Squared value
- O is an observed value
- E is an expected value
As you can see from the formula, the bigger the difference between an observed value and an expected value, the bigger the Chi-Squared value itself will be.
In terms of the procedure for performing a Chi-Square test, there are a couple of steps to go through. Although it depends on the type of test you would like to perform, the general framework still looks the same:
- Step 1: Create a table of your categorical variables and include your observed and expected frequencies of those variables. This is considered as the most challenging part of the test, as it is hard to determine the expected values of your categories.
- Step 2: Use the given formula to calculate the Chi-Square value with the numbers from your table.
- Step 3: Check the result of your Chi-Square value and find it in the chi-square critical value table – choose your appropriate “significance value” to determine your column and “degrees of freedom” to determine your row. That way, you can find the “Critical Chi-Square Value” for comparison.
- Step 4: Compare your Chi-Square value with the Critical Chi-Square value to determine the relationship of your categorical variables – if your value is lower, then the hypothesis is not rejected.
There are also lots of other online tools and software available to accurately determine your Chi-Square Values and validate your assumptions without having to use this formula by hand.
Benefits of Using Chi-Square Test in Marketing
One of the most significant benefits that the Chi-Square Test offers to market researchers is that it is relatively easier to perform calculations and determine statistical trends between the segments in which you have a business interest.
At the same time, with its numerical values, you can clearly spot the differences between two or even more groups of participants, making it more efficient to validate your assumptions and prove your hypothesis with clear comparison tables.
Furthermore, the essence of the Chi-Square Test is that it works with categorical data, eliminating the need to make any assumptions about the exact parameters of the population distribution.
How Can PRNEWS.io Help?
Doing proper research on your customer segments and understanding common patterns through the Chi-Square Test can be beneficial for any business out there.
But, besides doing thorough research on their behavior, it is also important to find appropriate channels to reach this audience and tell them all about your offerings.
Enter PRNews.io – a platform that has helped multiple companies worldwide efficiently maximize the outcomes of their press releases and get guaranteed placements for sponsored content in international online publications.
Getting more online visibility and attracting potential customers has never been easier!
If that sounds interesting, take a look at the list of our news sources for your potential placements, and reach out to us in case you have any questions.
FAQ
When to Use the Chi-Square Test?
Whenever you are doing market research and trying to determine the correlation between two or more categorical variables, the Chi-Square Test is an efficient way to make accurate assumptions about your hypothesis on that research.
What Are the Main Types of Chi-Square Tests?
There are two main types of Chi-Square Tests – “goodness of fit test” and “test of independence.” Both of these tests are used to accomplish different objectives in market research.
How to Do a Chi-Square Test?
You can execute the Chi-Square Test by following its formula and getting values from the table of your expected and observed values of categorical variables you’d like to compare.
