# CHISQ.INV Excel

## What Is CHISQ.INV Excel Function?

The CHISQ.INV Excel function is categorized under the statistical function used to calculate the inverse of the chi-squared distribution. This distribution is commonly employed in hypothesis testing.

The CHISQ.INV function takes three arguments: The value probability at which you want to calculate the density function of the chi-square distribution. The degrees of freedom are denoted by deg_freedom.

In the following example, we will calculate the probability of a chi-square value equal to 0.9 with 10 degrees of freedom using the CHISQ.INV Excel function.

Enter the formula =CHISQ.INV(B1, B2), and the result is obtained as shown in the image below.

###### Key Takeaways
• The CHISQ.INV function is a versatile tool that enables professionals to make well-informed decisions using the variability and association between categorical variables within a dataset.
• It was introduced in Excel 2010 and is not available in earlier versions.
• Note that the CHISQ.INV Excel function uses the complex statistical calculations. Its application extends across various fields, including finance, healthcare, and research data against expected results.
•  To understand and effectively utilize the CHISQ.INV function’s statistical analysis capabilities within Excel, see the working with categorical data or conducting research used in chi-square tests often employed in fields such as economics, sociology, and market research.

### Syntax

• Probability – This is the required argument. This is the value at which the chi-square distribution is to be evaluated.
• Deg_freedom – This is the required argument.  This is the value referred to as the “number of degrees of freedom,” which is a necessary parameter in our analysis. It is an integer value falling within the range of 1 to .

### How To Use CHISQ.INV Function In Excel? (With Steps)

To effectively utilize the CHISQ.INV function in Excel: follow these steps.

#### #1 – Access From The Excel Ribbon

Step 1: Choose the empty cell which will contain the result. Go to the Formulas tab and click it.

Step 2: Select the More Functions option from the menu.

Step 3: Select the Statistical option from the drop-down list. Select CHISQ.INV from the drop-down menu.

Step 4: A window called Function Arguments appears. As the number of arguments, enter the value in the probability and deg_freedom.

Select OK.

#### #2 – Enter The Worksheet Manually

Step 1: Select an empty cell for the output. Type =CHISQ.INV() in the selected cell. Alternatively, type =C and double-click the CHISQ.INV function from the list of suggestions shown by Excel.

Step 2: Press the Enter key to get the result.

### Examples

#### Example #1

Let’s examine an example to gain a better understanding of how the CHISQ.INV function operates in Excel. This function is the inverse of the chi-square function when given a probability value that is less than or equal to 0.2 and 1 degree of freedom.

To effectively utilize the CHISQ.INV function in Excel, it is crucial to follow these steps:

Step 1: Begin by selecting cell B3, where we will enter the formula.

Step 2: Enter the formula in the designated cell using the provided values:

=CHISQ.INV(B1, B2)

Step 3: As a result, you will obtain a value of 0.0642, accompanied by a visual graphical representation, as shown in the image below.

#### Example #2

In the following example, we will explore the functionality of the CHISQ.INV function in Excel. This particular function serves as the inverse of the chi-square function, specifically when provided with a probability value that is less than or equal to 0.05 and 5 degree of freedom.

To effectively harness the power of the CHISQ.INV function in Excel, it is imperative to adhere to the following steps:

Step 1: Commence by selecting cell B3, which will serve as the destination for our formula.

Step 2: Input the formula into the designated cell, utilizing the provided values:

=CHISQ.INV(B1, B2)

Step 3: Press the Enter key to obtain a value of 1.1455, accompanied by a visually appealing graphical representation, as depicted in the image below.

By following these steps, you will be able to utilize the CHISQ seamlessly.INV function in Excel, enhancing your data analysis capabilities.

#### Example #3

In this example, we will delve into the CHISQ.INV function in Excel and how to calculate various values of Probability and degrees of freedom. We will start with values ranging from 0.20 to 0.4 and 9 to 1.

To effectively utilize the CHISQ.INV function in Excel, it is essential to follow these steps:

Step 1: Begin by selecting cell B3, where we will input the formula.

Step 2: Input the formula in the designated cell using the provided values:

=CHISQ.INV(B1, B2)

Step 3: The result will be displayed below, accompanied by a visually appealing graphical representation showcasing the differences in values of probability and degrees of freedom, as depicted in the image below.

By following these steps, the CHISQ.INV function in Excel accurately calculates the given scenarios.

### What Is The Difference Between CHISQ.INV Function And CHISQ.DIST Function In Excel?

The difference between the CHISQ.INV function and the CHISQ.DIST function in Excel lies in their respective purposes and outputs.

• The CHISQ.DIST function calculates the probability density of a chi-squared distribution, which is commonly used to determine statistical significance in hypothesis testing. By providing arguments such as degrees of freedom and cumulative value, this function returns the probability that a variable lies within a certain range. Whereas the CHISQ.INV function works in reverse by calculating the inverse of this probability distribution. It provides the critical value for a given cumulative probability, allowing users to determine if their observed test statistic exceeds or falls below an acceptable threshold.
• While both functions are statistical analysis functions, they are used for different purposes: CHISQ.DIST enables calculations within a specific range, while CHISQ.INV supports tail risk assessment and decision-making based on predefined thresholds.

### Important Things To Note

• The “deg_freedom” argument is not an integer; MS Excel will truncate it.
• When a non-numeric value is entered, the “#VALUE!” will occur, indicating that MS Excel is unable to recognize it as a numerical value.
• The “#NUM!” will occur when:

-The probability value is less than zero or greater than one.

-The “degrees_freedom” argument is less than 1 or greater than 10.

Explain CHISQ.INV Excel function with an example.

The purpose of the CHISQ.INV Excel function is to calculate the inverse of the chi-square distribution. In the following example, we have three sets of values that lead to the # NUM! Error and the # VALUE! Error. We will apply the CHISQ.INV Excel function and examine the error scenario.

Enter the formula =CHISQ.INV(B1, B2) in cells B3 to D3, and see the outcomes as stated below.

What are the benefits of using the CHISQ.INV Excel function?

The CHISQ.INV Excel function is beneficial for statisticians, data analysts, and researchers who work extensively with statistical hypothesis testing. Using the CHISQ.INV Excel function, they can determine critical values needed to make decisions regarding the acceptance or rejection of null hypotheses based on observed data. This function probability and confidence intervals are related to chi-square distributions, which is crucial when analysing categorical data or conducting goodness-of-fit tests.

What are the limitations of using the CHISQ.INV Excel function?

• The function requires the input of the desired probability level at which the inverse chi-square value is calculated. This can be problematic as users may struggle to accurately determine the appropriate probability level without prior knowledge or access to relevant statistical tables.
• The CHISQ.INV Excel function has a limit on its inputs; it cannot enter negative values or probabilities greater than 1. This limits its applicability in scenarios involving negative or extreme probabilities.
• The CHISQ.INV Excel function assumes independent observations, and random sampling assumptions are violated; the function’s results are invalid or misleading.