The purpose of statistics are to summarize some quality or aspect of data (descriptive statistics) and to make inferences from data to populations (inferential statistics). The quality could just be something about a single variable or it could be about relationships among several variables. As soon as we make inferences, we must introduce the laws of probability. You have already been doing that in working with sampling error.

Sometimes statistics are just numbers and sometimes they are pictures, graphs, and charts that have numbers associated with them. The idea is to take incomprehensible piles of raw data and transform them into understandable statistics that help us make sense of the complex world around us.

Corbett does a good job in talking about several of the most common kinds of descriptive statistics: frequency, percentage distributions, measures of central tendency, and measures of variability. We will do a couple of examples of standard deviation in class and then do the lab exercises in chapter 8.