Degrees of Freedom in Chi-square Independence Test Solution

STEP 0: Pre-Calculation Summary
Formula Used
Degrees of Freedom = (Number of Rows-1)*(Number of Columns-1)
DF = (NRows-1)*(NColumns-1)
This formula uses 3 Variables
Variables Used
Degrees of Freedom - Degrees of Freedom is the number of values in the final calculation of a statistic that are free to vary. It varies based on the specific statistical test or analysis being conducted.
Number of Rows - Number of Rows is the count of horizontal divisions in a table or dataset. Each row typically represents a single observation, individual, or case in the dataset.
Number of Columns - Number of Columns is the count of vertical divisions in a table or dataset. In statistical analysis, it often refers to the number of variables or attributes being measured for each observation.
STEP 1: Convert Input(s) to Base Unit
Number of Rows: 5 --> No Conversion Required
Number of Columns: 3 --> No Conversion Required
STEP 2: Evaluate Formula
Substituting Input Values in Formula
DF = (NRows-1)*(NColumns-1) --> (5-1)*(3-1)
Evaluating ... ...
DF = 8
STEP 3: Convert Result to Output's Unit
8 --> No Conversion Required
FINAL ANSWER
8 <-- Degrees of Freedom
(Calculation completed in 00.004 seconds)

Credits

Creator Image
Created by Nishan Poojary
Shri Madhwa Vadiraja Institute of Technology and Management (SMVITM), Udupi
Nishan Poojary has created this Calculator and 500+ more calculators!
Verifier Image
Verified by Mona Gladys
St Joseph's College (SJC), Bengaluru
Mona Gladys has verified this Calculator and 1800+ more calculators!

Degrees of Freedom Calculators

Degrees of Freedom in Independent Samples t Test
​ LaTeX ​ Go Degrees of Freedom = Size of Sample X+Size of Sample Y-2
Degrees of Freedom in Chi-square Goodness of Fit Test
​ LaTeX ​ Go Degrees of Freedom = Number of Groups-1
Degrees of Freedom in Simple Linear Regression Test
​ LaTeX ​ Go Degrees of Freedom = Sample Size-2
Degrees of Freedom in One Sample t Test
​ LaTeX ​ Go Degrees of Freedom = Sample Size-1

Degrees of Freedom in Chi-square Independence Test Formula

​LaTeX ​Go
Degrees of Freedom = (Number of Rows-1)*(Number of Columns-1)
DF = (NRows-1)*(NColumns-1)

What is Degree of Freedom in Statistics?

In inferential statistics, we estimate a parameter of a population by calculating a statistic of a sample. The number of independent pieces of information used to calculate the statistic is called the degrees of freedom. The degrees of freedom of a statistic depend on the sample size. When the sample size is small, there are only a few independent pieces of information, and therefore only a few degrees of freedom. When the sample size is large, there are many independent pieces of information, and therefore many degrees of freedom.
Although degrees of freedom are closely related to sample size, they’re not the same thing. There are always fewer degrees of freedom than the sample size.
When we estimate a parameter, we need to introduce restrictions in how values are related to each other. As a result, the pieces of information are not all independent. To put it another way, the values in the sample are not all free to vary.

How to Calculate Degrees of Freedom in Chi-square Independence Test?

Degrees of Freedom in Chi-square Independence Test calculator uses Degrees of Freedom = (Number of Rows-1)*(Number of Columns-1) to calculate the Degrees of Freedom, Degrees of Freedom in Chi-square Independence Test formula is defined as the number of values in the final calculation of a statistic that are free to vary. It varies based on the specific statistical test or analysis being conducted in the chi-square independence test of given data sample. Degrees of Freedom is denoted by DF symbol.

How to calculate Degrees of Freedom in Chi-square Independence Test using this online calculator? To use this online calculator for Degrees of Freedom in Chi-square Independence Test, enter Number of Rows (NRows) & Number of Columns (NColumns) and hit the calculate button. Here is how the Degrees of Freedom in Chi-square Independence Test calculation can be explained with given input values -> 16 = (5-1)*(3-1).

FAQ

What is Degrees of Freedom in Chi-square Independence Test?
Degrees of Freedom in Chi-square Independence Test formula is defined as the number of values in the final calculation of a statistic that are free to vary. It varies based on the specific statistical test or analysis being conducted in the chi-square independence test of given data sample and is represented as DF = (NRows-1)*(NColumns-1) or Degrees of Freedom = (Number of Rows-1)*(Number of Columns-1). Number of Rows is the count of horizontal divisions in a table or dataset. Each row typically represents a single observation, individual, or case in the dataset & Number of Columns is the count of vertical divisions in a table or dataset. In statistical analysis, it often refers to the number of variables or attributes being measured for each observation.
How to calculate Degrees of Freedom in Chi-square Independence Test?
Degrees of Freedom in Chi-square Independence Test formula is defined as the number of values in the final calculation of a statistic that are free to vary. It varies based on the specific statistical test or analysis being conducted in the chi-square independence test of given data sample is calculated using Degrees of Freedom = (Number of Rows-1)*(Number of Columns-1). To calculate Degrees of Freedom in Chi-square Independence Test, you need Number of Rows (NRows) & Number of Columns (NColumns). With our tool, you need to enter the respective value for Number of Rows & Number of Columns and hit the calculate button. You can also select the units (if any) for Input(s) and the Output as well.
How many ways are there to calculate Degrees of Freedom?
In this formula, Degrees of Freedom uses Number of Rows & Number of Columns. We can use 3 other way(s) to calculate the same, which is/are as follows -
  • Degrees of Freedom = Size of Sample X+Size of Sample Y-2
  • Degrees of Freedom = Sample Size-1
  • Degrees of Freedom = Sample Size-2
Let Others Know
Facebook
Twitter
Reddit
LinkedIn
Email
WhatsApp
Copied!