MathBench > Statistical Tests

Goodness of Fit Tests

A brief recap of the Brute Force Method

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. Simulate lots of data We simulated 100 trials with the applet.
4. Decide what your "threshold of pain" is (otherwise known as a p-value). *Note: technically this should come before simulating your data! We picked a threshold of 5%, or 5 out of 100 trials
5. Determine whether the agreement of the simulated data with the observed data falls within the threshhold -- if so, we say the model fits the data well. Since the simulated data showed many more than 5% of trials with at least 42 mon/fri sickdays, we decide that the model (random sickdays) fits the data.