Match the following statistical terms with their best definitions. d. Scientific (or Alternative) Hypothesis e. Null Hypothesis (or null model) g. Type I Error a. Type II Error b. P-value c. Nonparametric statistics a. The error made by failing to reject a null hypothesis that is actually false; also called a false negative. b. Probability that the null hypothesis is false, given the experimental results. Put another way: the probability of committing a Type II error if one were to accept the null hypothesis, given the results. c. Statistical procedures performed on ranked observations. d. A statement about how you think something works, which leads to testable and falsifiable predictions that sample observations will differ among treatments or groups due to some factor, or are correlated with one or more predictor variables. e. The hypothesis that there is no real difference between sample observations and a treatment or a set of predictor variables; any observed differences are purely due to chance. This hypothesis is evaluated statistically. f. Probability that the null hypothesis is true, given the experimental results. Put another way: the probability of committing a Type I error if one were to reject the null hypothesis, given the results. g. The error made by rejecting a null hypothesis that is actually true; also called a false positive.