First, compare and contrast the four scales of measurement (nominal, ordinal, interval, and ratio) and identify examples of each (See Jhangiani Chapter 19). In the statistical analysis package we use (and almost everywhere else) interval and ratio are grouped together, and both are called "scale." Then, recall that with inferential statistics we are doing more than describing (as we do with percentages) we are inferring if our results from our sample are relevant to a larger population. The most common way we do this is to test the null using a p-value (see Jhangiani et al. chapter 57). Let's explore how statistics can be misleading even with significant findings in inferential statistics