Week 8: Analysis of Categorical Data

This set of flashcards covers key vocabulary and concepts related to the chi-square tests discussed in the lecture.

Chi-square goodness-of-fit test

A statistical test used to determine if a sample distribution differs from a known population distribution.

Null hypothesis (H0)

States that there is no effect or no difference; in chi-square, it typically states that the proportion of each category matches specified values.

Alternative hypothesis (H1)

The hypothesis that specifies a difference; in chi-square, it states that the distribution of the characteristic in the population is different from specified values.

Expected frequencies

The frequencies that would be expected in each category if the null hypothesis were true.

Degrees of freedom (df)

In chi-square tests, it is calculated as the number of categories minus one (k-1) for goodness-of-fit tests or (R-1)(C-1) for tests of independence.

Chi-square statistic (χ²)

A calculated value that measures how much observed frequencies deviate from expected frequencies.

Critical value

The threshold value that the test statistic must exceed in order to reject the null hypothesis.

Statistical significance

A measure of whether an observed effect is likely due to chance; often assessed using a p-value.

Random sample

A sample that is selected in such a way that every individual has an equal chance of being included.

Test of independence

A statistical test used to determine whether there is a significant association between two categorical variables.