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from PART 1 - DESCRIPTION
Published online by Cambridge University Press: 05 June 2012
Not everything that can be counted counts; and not everything that counts can be counted.
Albert EinsteinIntroduction
This chapter focuses on summarizing and describing patterns in data via tables. Tables efficiently convey basic summary information such as counts and averages. Tables can also be a powerful device with which to explore complicated relationships in data. Thus, the work on tables in this chapter will enable you to understand the concepts of the conditional average and regression analysis better. Tables make clear that a particular value can be viewed as the result of a conjunction of conditions or categories. That is a crucial aspect of regression analysis.
A powerful way to tabulate data is Excel's Pivot Table feature. A Pivot Table enables the user to try a variety of different views of the data. Pivot Tables, combined with Excel's formatting and charting, facilitate effective and clear data description.
The Basic Pivot Table
Workbooks: Indiana FT Workers.xls; Histogram.xla(Excel add-in)
Open the Excel file called Indiana FT Workers.xls (available in the folder Basic Tools\InternetData\CPS) to begin learning about Pivot Tables and tabulation. The file contains information on 598 people from the March 1999 Current Population Survey (CPS). The Doc sheet describes how the data were obtained, and the file CPS.doc in the same folder contains detailed instructions on downloading data from the CPS.
We do not approach the data in a vacuum. Prior questions guide our exploration of the data. For example, we might want to find out if more education is associated with higher income and, if so, how much more.
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