1.4-5 - Chi-Square Test, McNemar Test

Chi-Square Test

- Also called the X2 Tests

- Statistical procedure for determining the difference between observed and expected data

- Can also be used to decide whether it correlates to our data’s categorical variables

- Helps determine whether a difference between two categorical variables is due to chance or a relationship between them

Observed Data

- real numbers you gather from your survey or experiment

Expected Data

- what you would expect to see if there were no special relationship or pattern in the data – meaning if everything were purely random

One-Sample Goodness-of-Fit Test

- Used if there is one categorical variable

- Used to determine whether the distribution of cases in a single categorical variable follows a known or hypothesized distribution

Pearson’s chi-square goodness-of-fit test

- another term for the one-sample goodness-of-fit test

Chi-Square Test of Association

- Two categorical variables

- Used to discover if there is a relationship between two categorical variables

McNemar Test

- Used to determine if the proportions of categories in two related groups significantly differ form each other

- Used to analyze pretest-posttest (before and after) study designs and commonly employed in

Cochran’s Q Test

- used if you have more than two repeated variables