According to the chi square test, a hypothesis may be accepted if the difference between observed and expected results is __

Close to zero

Step-by-step explanation:

In chi Square test, we accept the hypothesis If the sum of the weighted squared deviations is small.

This is because If the sum of the weighted squared deviations is small, it will mean that the observed frequencies will be close in value to the expected frequencies and therefore, there would be no need to reject the the hypothesis. However, when the sum is large, there will be need to question the hypothesis or claim made.

Thus, the hypothesis may be accepted if the difference between observed and expected results is close to zero

b i think

step-by-step explanation:

not really sure