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Categorical Data Analysis
Collection of tools that you can use when your data are nominal scale
Chi-square goodness-of-fit
Categorical finds out how well the observed scores fit w the scores a particular model predicts
Always a one-sided test
Used when you have a table of observed frequencies of different categories, and the null hypothesis gives you a set of “known” probabilities to compare them to.
Expected Frequencies
if the null hypothesis were true, what would we expect to see?
(Chi-square) Distribution
Degrees of Freedom
number of “normally distributed variables” that I’m squaring and adding together
You calculate it by counting up the number of distinct “quantities” that are used to describe your data and then subtracting off all of the “constraints” that those data must satisfy
One-sided Test
Critical area of a distribution is one-sided so that it is either greater than or less than a certain value, but not both.
Yates Correction