Why use $\chi^2$ test to determine the presence of white noise?

1. What is Chi 2 test used for?
2. How do you test for white noise?
3. Can Chi-square be used to determine the strength of a relationship Why or why not?
4. How do you determine if Chi-square test is significant?

What is Chi 2 test used for?

A chi-square test is a statistical test used to compare observed results with expected results. The purpose of this test is to determine if a difference between observed data and expected data is due to chance, or if it is due to a relationship between the variables you are studying.

How do you test for white noise?

To test whether a set of samples can be well modeled as white noise, we may compute its sample autocorrelation and verify that it approaches an impulse in the limit as the number of samples becomes large; this is another way of saying that successive noise samples are uncorrelated.

Can Chi-square be used to determine the strength of a relationship Why or why not?

By itself, chi square helps us only to decide whether our variables are independent or related. It does not tell us how strongly they are related. Part of the reason is that the sample size and table size have such an influence upon chi square.

How do you determine if Chi-square test is significant?

You could take your calculated chi-square value and compare it to a critical value from a chi-square table. If the chi-square value is more than the critical value, then there is a significant difference.