Summary statistics are a collection of measurements that provide insight into a data set. Although the data sets that you have worked with in this course are relatively small, some data sets are enormous, with thousands of variables and millions of values. Summary statistics provide a simple means by which to characterize any data set, no matter what its size. Think of summary statistics as the vital signs of your data. Just like your vital signs (temperature, pulse, and blood pressure) provide insight into the state of your health based on a few simple numbers, the central tendency and spread of a data set provide basic information about the nature of a data set.
As you read the assigned chapter in the textbook, remember to focus on the concepts that are discussed, rather than getting bogged down in the mathematical formulas. Even the first formula presented in the chapter, used to calculate the mean, employs complex mathematical symbols to designate a simple concept. You do not need to decrypt sigma notation for a finite series to understand what an arithmetic mean is. You simply need to know that a mean is equal to the sum of the data divided by the number of data points. Then, you unleash the power of SPSS to calculate all of that for you.