##### Definition:

Statistical significance is used to find whether the given data is reliable or not and it does not have any decision-making utility. It's based on Comparative Error and difference between percentages for the given statistical data.

#### Formula:

Comparative Error = 1.96 * √ (r1(100-r1) ÷ s1) + (r2(100-r2) ÷ s2)
##### Example:

Find the significance occurrence for the sample sizes of 50, 75 and the respective percentage response for the sizes are 5% and 10%.

##### Given,

Sample size (s1) = 50
Sample size (s2) = 75
Percentage Response (r1) = 5%
Percentage Response (r2) = 10%

##### To Find,

Significance status

##### Solution:

Let us learn how to calculate the value of significance status. First, we need to calculate comparative error and percentage difference for the given statistical data.

###### Step 1:

Substitute the given values of s1, r1, s2, r2 in the formula of comparative error,
Comparative Error = 1.96 * √ (r1(100-r1) ÷ s1) + (r2(100-r2) ÷ s2)
= 1.96 * √ (5(100-5) ÷ 50) + (10(100-10) ÷ 75)
= 1.96 * √ (475 ÷ 50) + (900 ÷ 75)
= 1.96 * √ (9.5) + (12)
= 1.96 * √ 21.5
= 1.96 * 4.6369
= 9.09

###### Step 2:

Now, find the percentage difference of r1 and r2,
= absolute (r1-r2)
= absolute (5% - 10%)
= 5%

###### Step 3:

If difference is greater than the comparative error then significance occurs.
Else, it doesn't occur.
In this problem comparative error = 9.09 and percentage difference = 5.
The value of comparative error is greater than the difference. So significance does not occur here.