Ap Stats Unit 9.1 Stuff

im so cooked for stats

P-values

α, significance level

Assuming [H₀], the probability of getting [statistic in context or more extreme] in a sample size of [n from this population] is [p-value]

When p-value < α

Since the P-value = [value] < α = [alpha level], we reject the H₀. There is convincing evidence that [H_a in context].

When p-value > α

Since the P-value = [value] > α = [alpha level], we fail to reject the H₀. There is not convincing evidence that [H_a in context].

Type I and II Errors

We decide _____ when in reality _____ is true.

Null hypothesis

H₀ : parameter = value

(parameter MUST be p or μ)

(add units if applicable)

Alternative hypothesis

H_a : parameter > value

H_a : parameter < value

H_a : parameter ≠ value

(parameter MUST be p or μ)

(add units if applicable)

Small vs. Large p-value

Small P-values: evidence against H₀

Large P-values: fails to give convincing evidence against H₀

(NEVER accept the null hypothesis)

Consequences of Type I and II errors

These are not the definitions of Type I and Type II errors. They are what happens as a result of making that decision.