The level of significance (alpha) associated with testing a null hypothesis is also referred to as the probability of a Type I error. Alpha is the probability of rejecting the null hypothesis on the basis of your sample data when it is, in fact, true for the population you are interested in. Since alpha concerns the probability of making a mistake in your analysis, should you always try to set the value as small as possible? Why or why not?