Quant: Hypothesis Testing

Null Hypothesis (H_0)

statement of no difference between variables – they are not related

Alternative Hypothesis

claim about population that is contradictory to the null hypothesis and what we conclude when we reject it

Type I Errors

occurs when a researcher rejects the null hypothesis even though it is true

Type II Errors

occurs when a researcher fails to reject the null hypothesis even though it is false

Normal Distributions

test claims about a population mean or proportion when conditions for a z-test are satisfied

Student T-distribution

used to test a population when population sdev is unknown and sample is  < 30

Chi-square Distribution

tests whether categorical variables are associated or whether observed category frequencies differ from expected frequencies

Hypothesis Testing - One Variable

examines whether a single characteristic of a population differs from specific value or meets claim

Hypothesis Testing - Two Variables

examines whether a relationship, association, or difference exists between 2 variables