alpha or alpha level alternative hypothesis beta common zone critical value hypothesis hypothesis testing nonrobust assumption null hypothesis one-tailed hypothesis test p value power rare zone robust assumption significance level statistically significant two-tailed hypothesis test Type I error Type II error | the error that occurs when we fail to reject the null hypothesis but should have rejected it; p(Type II error) = β. an assumption for a statistical test that can be violated to some degree and it is still OK to proceed with the test. abbreviated H1; a statement that the explanatory variable has an effect on the outcome variable in the population; usually, a statement of what the researcher believes to be true. the probability of rejecting the null hypothesis when the null hypothesis should be rejected. a proposed explanation for observed facts; a statement or prediction about a population value. a statistical procedure in which data from a sample are used to evaluate a hypothesis about a population. the section of the sampling distribution of a test statistic in which it is unlikely an observed outcome will fall if the null hypothesis is true; typically, 5% of the sampling distribution. abbreviated H0; a statement that in the population the explanatory variable has no impact on the outcome variable. the section of the sampling distribution of a test statistic in which the observed outcome should fall if the null hypothesis is true; typically, 95% of the sampling distribution. the probability of Type I error; the same as alpha level or significance level. the error that occurs when the null hypothesis is true but is rejected; p(Type I error) = α. hypothesis that predicts the explanatory variable has an impact on the outcome variable but doesn’t predict the direction of the impact. when a researcher concludes that the observed sample results are different from the null-hypothesized population value. the probability of making a Type II error; abbreviated β. the probability of Type I error; the same as alpha level or p value. hypothesis that predicts the explanatory variable has an impact on the outcome variable in a specific direction. the value of the test statistic that forms the boundary between the rare zone and the common zone of sampling distribution of the test statistic. the probability of making a Type I error; the probability that a result will fall in the rare zone and the null hypothesis will be rejected when the null hypothesis is true; often called significance level; abbreviated α; usually set at .05 or 5%. an assumption for a statistical test that must be met in order to proceed with the test. |