Chi^{2 }Test (goodness of fit)

X^{2} test is a test of distributions

Think of it as a way to compare histograms

You will compare one set of data to "what you expected
to get"

Test statistic = X^{2} = Sum of __(observed
– expected) ^{2}__

expected

Look up the critical value

df = degrees of freedom = number of categories – 1

Reject null hypothesis if X^{2} > critical
value of X^{2}