**PEARSON CHI SQUARE TEST USING SPSS …..**

**an easy task….**

Pearson chi square test also called as chi square test for independence or chi square test of

association is used to find whether there is a relationship between two categorical variables.

To carry out chi square test, null hypothesis is considered first. In SPSS, when cross

tabulation is done and two variables are considered, null hypothesis is made. Null hypothesis

states that no association exists between the two cross tabulated values considered and thus

the variables are statistically independent. For example, if 2 methods are compared to find out

which one is better and statement is made that both methods are equally good then this is

called as null hypothesis. If it is proposed that two variables are related then it is considered

as alternative hypothesis. For example, if one method is superior than the other, then called as

alternative hypothesis. Through cross tabulation and statistics involved in it, chi square value

table including significant difference value is calculated and studied to find the acceptance or

rejection of null hypothesis. If significant difference is less than 0.05 (generally taken

between 0-1) then null hypothesis is rejected which means there is a relationship between the

two variables considered. Significant difference is generally looked at 0.05 which denotes

that the confidence level is 95%, it can be taken at any value between 0-1. If significant

difference is more than 0.05, then null hypothesis is accepted, which signifies that there is no

relationship between the two variables considered.

Example : Null hypothesis – Area of residence and BMI (Body mass index) are

independent.

Alternative hypothesis- Area of residence and BMI are dependent.

Or Null hypothesis- There is no association between living in an urban area and being

overweight.

i.e. It is not that people living in urban area are overweight than people living in rural area.

Here, significance level is 0.05 is taken. Cross tabulation using SPSS is done, in which

people residence is taken in rows and weight category is taken in columns. Statistics is

applied and chi square table including significant difference is studied. In this example,

significant value in pearson chi square is obtained as 0.0001 which is much less than 0.05

and thus signifies that null hypothesis is rejected i.e. two variables considered (weight and

residential area ) are strongly related than people living in urban area are overweight than

people in rural area.

By

Shailja Talwar