Chi-squared Test

Discontinuous data Eye colour, tongue rolling how many individuals fall into a particular category test whether the number of individuals in different categories fit a null hypothesis (an expectation of some sort).

A simple example Suppose that the ratio of male to female students in the Science Faculty is exactly 1:1, but in the Pharmacology Honours class over the past ten years there have been 80 females and 40 males. Expected is 60 of each but Observed is 80:40

FemaleMaleTotal Observed Expected Always same as observed total O - E must always be zero

(O – E) (O – E) E 6.676,67X 2 = Use the X2 value for the table.

Degrees of freedom n – 1 where n is the number of categories We have two categories n – 1 = 1

From the x2 table, we find a "critical value of 3.84 for p = we have a significant difference from the expectation.

Example with genetics 80 fruit flies 40 red eyes, normal wing 20 white eyes, normal wing 16 red eyes, stubby wings 4 white eyes stubby wing Expected ratios 9:3:3:1