7. Data Analysis I

Data is collected daily from a variety of sources for the purpose of providing information. Once you have collected data, what will you do with it? Data can be described and presented in many different formats. For example, suppose you are interested in buying a house in a particular area. You may have no clue about the house prices, so you might ask your real estate agent to give you a sample data set of prices. Looking at all the prices in the sample often is overwhelming. A better way might be to look at the median price and the variation of prices. The median and variation are just two ways that you will learn to describe data. Your agent might also provide you with a graph of the data.
In this chapter, you will study numerical and graphical ways to describe and display your data. You will learn how to calculate, and even more importantly, how to interpret these measurements and graphs. A table can be used to collect and organize data which can then be more easily analyzed to determine patterns or trends. Frequency distributions and stem-and-leaf plots provide a tabular view that can be more revealing than a basic table. A graph is a tool that helps you learn about the shape or distribution of a sample or a population. A graph can be a more effective way of presenting data than a mass of numbers because we can see where data clusters and where there are only a few data values. Newspapers and the Internet use graphs to show trends and to enable readers to compare facts and figures quickly. Statisticians often graph data first to get a picture of the data. Then, more formal tools may be applied. Some of the types of graphs that are used to summarize and organize data are the bar graph, the histogram, the frequency polygon (a type of broken line graph), the pie chart, and the box plot.
In this chapter, we will look at ways to collect, present and describe data. We will also consider how data can be presented in misleading ways.