MathBench > Statistical Tests

Goodness of Fit Tests

Summary of chi-square:

Here's a summary of the steps needed to do a chi-square goodness of fit test:

General Steps

In the Dilbert example...

1. Decide on a null hypothesis -- a "model" that the data should fit Dilbert's null hypothesis was that the sickdays were randomly distributed.
2. Note your "expected" and "observed" values Since 40% of weekdays fall on Monday or Friday, the same should be true of sickdays -- or 40 out of 100. The observed value was 42 out of 100.
3. Calculate the chi-square [add up (o-e)2 / e ] We got 0.166
4. Look up the chi-square-crit based on your p-value and degrees of freedom. With p=0.05 and df=1, chi-square-crit = 3.84.
5. Determine whether chi-square-calc < chi-square crit-- if so, we say the model fits the data well. Chi-square-crit > chi-square-calc, so the deviations are small and the data fit the null model of random sickdays.