ADVERTISEMENT
FEEDBACK

Adblocker Detected

ad
Uh Oh! It seems you’re using an Ad blocker!

We always struggled to serve you with the best online calculations, thus, there's a humble request to either disable the AD blocker or go with premium plans to use the AD-Free version for calculators.

Disable your Adblocker and refresh your web page 😊

Chi-Square Calculator

Chi-Square Calculator

Enter the observed and expected values of the variable and the tool will find the chi square values.

Observed value :

Expected value :

ADVERTISEMENT

Table of Content

Get the Widget!

Add this calculator to your site and lets users to perform easy calculations.

Feedback

How easy was it to use our calculator? Did you face any problem, tell us!

The Chi square calculator will help you to compare observed and expected values in a data set that tells you how validate the data set is. Get instant solutions with steps involved. The chi-squared calculation is one of the most reliable methods to know the effectiveness of the correlation.

What Is a Chi-Square Statistic?

The chi-square statistic (χ²) is a statistical measure to test the correlation or the relationship between the expected and observed variable. 

The Chi-Square values are mutually exclusive to represent the effect of independent and dependent variables.

For example, check the price elasticity and inelasticity relative to the demand for the product and services. The cause and effect of the observed and expected values are evaluated with the assistance of the Chi-Square Statistic calculator in a given marketplace.

The Chi Square Formula:

The chi squared formula is:

χ^2 = ∑(O_i – E_i)^2/E_i

Here,

O_i = Observed value

E_i = Expected value

The chi square analysis calculator is a test for the dependence of the two qualitative variables.

Practical Example:

Let’s calculate chi square the observed value is 15 of a variable and the expected value is 10, then what is the chi-square (χ^2) statistics test value?

Given:

Observed value = 15 

Expected value = 10

Chi square expected value (χ^2) =?

Solution:

The chi square equation is given below: 

χ^2 = ∑(O_i – E_i)^2/E_i

χ^2 = ∑(15 – 10)^2/10

χ^2 = 2.5

The chi squared calculator assists in gauging the difference between the observed values and the expected value. The chi square analysis is to know the real-time regression relation between the probabilities of occurrence.

How Chi-Square Calculator Serve You?

A chi-square test calculator serves as a valuable tool in statistical analysis, especially when you want to assess the independence or association of two variables.

Chi-Square Value(χ²):

  • The Chi-square value(χ²) is critical in testing the correlation of two variables and testing the deviation of the variable from the actual value vs. observed values.
  • The Chi-square value(χ²) interprets the significance relation between the dependent and independent variables.

You need to calculate chi square value to interpret the real-time relation on the regression line

FAQs:

What Is a Good Chi-Square Value?

The expected frequency should be at least 5 or above to be best for the correlation of variables. It is necessary to calculate the chi square value on the basis of expected and observed comparison with our chi square test statistic calculator.

What Is the Difference Between the T-Test and Chi-Square?

The t-test is used when you have a dependent quantitative variable and an independent categorical variable. A chi square table calculator is used when you have two categorical variables that relationship among themselves. 

What Are the Categorical Variables?

A categorical variable is qualitative in nature and is a variable that can take on one of a limited, and usually not fixed, number from the probability of outcomes. 

The chi square calculator enables us to know the relationship between this categorical variable. 

Examples are 

  • The expected blood type of a person or group of people: A, B, AB, or O.
  • The probable type of rock: Igneous, Sedimentary, or Metamorphic.

The chi squared formula is the extraction of the qualitative variables, not the quantitative variables. 

References:

From the  of Wikipedia: Chi-squared test, History

From the start of BMJ.com: Chi-Test, T-test