# CHISQ.TEST Excel

## What Is CHISQ.TEST Excel Function?

The CHISQ.TEST Excel function is a statistical function used to test the independence of two categorical variables in a data set. It calculates the p-value associated with the chi-squared statistic, which measures how likely it is that any observed differences between the variables are due to random chance rather than a true relationship. The CHISQ.TEST Excel function not only streamlines the testing process but also ensures accuracy and objectivity in statistical analyses.

In the following example, let us look at the CHISQ.TEST Excel function and how it works. Here, we have two sets of values: the actual and the expected. Apply the formula below in cell C6 to get the result.

= CHISQ.TEST(A2 :B4,D2 :E4)

You get a result of 0.42 or 42% as a relation between the two sets of values, which shows that they are quite far apart from each other.

### Syntax

Actual_range – (Mandatory) This is a data set with the observed values..

Expected_range – (Mandatory) This is a range of data showing the expected frequencies or counts.

The CHISQ.TEST function in Excel calculates the probability that observed data fits a specific distribution. It requires the actual and expected data ranges and compares them using a chi-squared test. It returns a p-value indicating the likelihood of differences occurring by chance. This information is useful for decision-making in fields like finance, healthcare, and market research.

###### Key Takeaways
• The CHISQ.TEST function in Excel is used to calculate the chi-square distribution of two datasets of observed and expected frequencies.
• The syntax of the function is; =CHISQ.TEST(actual_range,expected_range).
• The function helps determine if differences between the two sets are due to sampling error.
• The CHISQ.TEST function is only available in Excel 2010 and newer versions. It is an improved version of the CHITEST function.

### How To Use CHISQ.TEST Excel Function in Excel?

To use the CHISQ.TEST Excel function in Excel effectively, follow these steps.

#### #1 – Access from the Excel ribbon

Step 1: To show the result in a specific cell, select an empty cell and click on the Formulas tab.

Step 2: From here, select More Functions.

Step 3: Choose the Statistical option and then select CHISQ.TEST from the drop-down list.

Step 4: Now, fill in the actual_range and expected_range fields in the Function Arguments window and then click OK.

#### #2 – Enter the worksheet manually

Step 1: To designate an empty cell for the output of the CHISQ.TEST function in Excel, you can either enter the formula with the required arguments directly in the desired cell (for e.g., =CHISQ.TEST(A1:B1, A2:B2)), or type =C and then double-click on CHISQ.TEST from the list of suggestions.

Step 2: To get the result, type in the arguments, close the braces and hit Enter.

The manual equation for the above is;

This statement describes a statistical analysis method where;

‘r’ represents the number of rows,

‘c’ represents the number of columns,

‘Oij’ is the observed frequency in a specific cell where the row is ‘i’ and the column is ‘j,’

‘Eij’ is the expected frequency in the same cell.

### Examples

Now, let us look at some examples to understand the CHISQ.TEST function in Excel.

#### Example #1

The chi-square test was done using the CHISQ.TEST Excel function helps determine the relationship between the values in a sample. This scenario can be used to analyze the enrolment of men and women in three games at a particular place to see if the proportions are significantly different.

Step 1: Insert the following chi-square test formula in the cell D7 to attain the result.

=CHISQ.TEST(B3:C5,F3:G5)

Step 2: The test result is reflected in the cell D7, as shown below.

When the analysis checked the enrolment rates of men and women in three specific games to determine if there were any significant differences in the proportion of participants, the result obtained was 0.00213695. Since the probability is less than 0.05 or less, it indicates a significant difference between the observed and the expected values of the participants.

#### Example #2

The chi-square test is done in Excel using the CHISQ.TEST Excel function determines if values in a sample are statistically independent. This test helps us understand the relationship between variables and make better decisions based on data. This example can be used to compare the actual votes of men and women to expected votes in different districts to see if the proportions are significantly different or as expected.

Step 1: To use the CHISQ.TEST Excel formula, select cell D6 and enter the formula as shown.

=CHISQ.TEST(B3:C4,F3:G4)

Step 2: Press enter to see the result in cell D6.

When votes are checked, if the actual votes of men and women in different districts match the expected votes, the result executed is 0.47980. It shows that there is not a significant association between the actual and expected frequencies.

#### Example #3

The chi-square test in Excel using the CHISQ.TEST Excel function compares the actual distribution of values in Team 1 and Team 2 to an expected distribution to see if they are significantly different.

Let’s start the calculation by entering the values as prescribed below;

Step 1: Insert the formula to calculate the chi-square test in cell D7. The complete formula is =CHISQ.TEST(B3:C5,F3:G5)

Step 2: The outcome is executed in cell D7.

### Important Things To Note

• The CHISQ.TEST Excel function is user-friendly, can be used with nominal data, and does not require any assumptions about the data distribution.
• The #DIV/0! error happens when any of the values in the expected range are zero.
• The #N/A error happens when the data arrays have different dimensions or contain only one value. This means the length and width of the arrays are equal to 1.
• The #NUM! error occurs when a negative value is included in the expected range.
• It is utilized in fields such as social sciences, market research, and quality control to assess relationships between variables and make informed decisions based on data analysis.

1. What does the CHISQ.TEST function test for in Excel?

The CHISQ.TEST function in Excel is used to test for independence between categorical variables. It calculates the observed frequencies of one variable are independent of another variable, by comparing the observed frequencies with expected frequencies under a given null hypothesis independence, the CHISQ.TEST function produces a p-value that indicates whether there is a significant relationship between the variables. A low p-value suggests that it is unlikely that the variables are independent, while a high p-value indicates no significant association.

2. What are the limitations of using the CHISQ.TEST function in Excel?

The limitations of using the CHISQ.TEST function in Excel are;
The function can only be used for hypothesis testing with two variables. If there are more than two variables or categories, there should be separate chi-squared tests for each pair of variables, which can be time-consuming and cumbersome.
The CHISQ.TEST Excel function assumes that the data is independent and identically distributed, which may not always be the case in real-world scenarios.
The function cannot handle missing values or non-numeric data, so data cleaning and manipulation may be necessary before using the function.

3. What are the benefits of using the CHISQ.TEST function in Excel?

The benefits of using the CHISQ.TEST function in Excel are;
Professionals who use this function can test the independence of variables in contingency tables, evaluate relationships between categorical variables, and perform goodness-of-fit tests with ease and accuracy.
The CHISQ.TEST function also provides users with a clear understanding of the significance level of their results, enabling them to draw meaningful conclusions from their analyses.