a. The Null Hypothesis The null hypothesis is a starting point or reference point for hypothesis testing (finding out whether certain differences or effects are due to random chance). It says that, unless proven otherwise, any differences or effects we might see in a particular study or experiment are due to random chance. For instance, the null hypothesis for a new drug study might be that the drug actually has no effect on the disease relative to a placebo. b. Type I (Alpha) Error A Type I error refers to rejecting the null hypothesis when it is, in fact, true. It is also called a 'false positive' because it signifies that an effect or difference is observed when there is none. We commonly assign a probability of alpha () to a Type I error. That is, we set the significance level at 0.05, so that a maximum of 5 per cent of the time we will reject the null hypothesis in error. c. Sampling Distribution A sampling distribution is the probability distribution of a certain statistic for the many different possible samples of the same size from a population. A sampling distribution is the distribution of what a statistic would