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Chi-Square Test is used to see if there is an association between the categorical variables or not. We formulate two hypothesis.

**Null Hypothesis:** There is no significant relationship between variables.

**Alternative Hypothesis:** There is a significant relationship between variables.

O - Observed Frequency

E - Expected Frequency

Significance Levels α = 0.01, α = 0.05, α = 0.10

Chi-Square Critical value is obtained from Chi -table using Degree of freedom and Significance level α.

If the **chi calculated > chi critical or p-value < 0.05 (decided significance level)**, we Reject the Null Hypothesis. We state there exist significant relationship between the variables.

In the above mentioned Example **Chi Square Calculated value is 624.37**.

Chi Square Critical Value at Alpha = 0.01, 0.05, 0.10 is less then Chi Square Calculated value.

Here **Chi Calculated > Chi Critical**. Hence we state there exist a significant relationship between variables.

In the above example the Chi Calculated value > Chi Critical

480.70>24.725 at alpha = 0.01

480.70>19.675 at alpha = 0.05

480.70>17.275 at alpha = 0.10

Hence we reject the Null hypothesis and state that there exist significant relationship between all 3 variables(Gender, Age and Drink). As there is relationship between 3 variables we can go for cell comparison test which will highlight the cell.