α = P(Type I Error) (level of significance)
β = P(Type II Error)
After assessing the consequences of Type I and Type II errors, we identify the largest α that is
tolerable for the problem. We then employ a test procedure that uses α as the maximum
acceptable Type I error rate.
Generally, with everything else held constant, decreasing one type of error increases the
The only way to decrease both types of errors is to increase the sample size.
No matter what decision is reached through a hypothesis test, there is always the risk of
one of these errors.
Test statistic – a numeric function of sample data on which a conclusion to reject or fail
to reject H0is based
P-value – the probability of obtaining a test statistic as extreme or more extreme than the
one calculated, assuming H is t0ue
A decision to reject H 0s found by comparing the p-value to α.
If p-value ≤ α, H 0s rejected
If p-value > α, H is not rejected
Steps of Hypothesis Testing (7-step procedure)
State the set of hypotheses that correspond to the research question of interest in terms
of the population parameter(s). H /H
Select the significance level α. This is the cut-off point for deciding if the probability is
small enough (i.e., is p-value small enough?