Interpreting Hypothesis Tests
The t-test is used to compare mean values between two different groups.
The Chi-square test is used to compare proportions between two different groups.
The ANOVA test is used to compare mean values across multiple groups.
A type I error occurs when a hypothesis test declares a result to be statistically significant when in fact no true effect or association exists in the population.
Replication of study findings is an effective method for addressing type I errors.
The Bonferroni correction addresses the problem of multiple comparisons by setting a more stringent p-value threshold for statistical significance.
A type II error occurs when a hypothesis test declares a result to be statistically insignificant when in fact a true effect or association exists in the population.
Power is the pre-specified probability that a particular study will not make a type II error.
- 9.Power increases with
A larger sample size
Decreased variability of measurements within individuals
A greater pre-specified effect or association