Hypothesis testing Flashcards
7 steps of hypothesis testing
- state null and alt hypotheses
- set decision criteria (level of significance)
- establish critical values using decision criteria
- draw random sample/calculate mean
- calculate SD and SE
- calculate Z or T score
- compare calculated Z or T score to critical values
area of acceptance
if sample mean falls in this area, accept null hypothesis
area of rejection
if sample mean falls in this area, reject null hypothesis
level of significance (a)
probability of rejecting a null hypothesis when it is true (type I error)
type I is also called-
false positive error (accepting alt hypothesis when it is false)
power of test
ability to avoid type II error
type II error is also called-
false negative error
Power increases as (5)
- level of significance increases
- critical region increases
- size/difference between sample mean and hypothesized mean increases
- sampling error decreases
- sample size increases
P value is the
probability value
most important non-pareometric test
Chi-square
__ tailed tests are more powerful than ___ tailed tests
one; two
when testing directional hypotheses, there is ___ area of rejection
one
chi-sqaure tests:
proportions, tells us whether the proportions of observations falling in different categories differ significantly from those that would be expected by chance
