Statistical Analysis with Excel For Dummies. Joseph Schmuller

Statistical Analysis with Excel For Dummies - Joseph Schmuller


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with Excel graphics

       Determine central tendency and variability

       Work with standard scores

       Understand and visualize normal distributions

      Show-and-Tell: Graphing Data

      IN THIS CHAPTER

      

Introducing graphs

      

Working with Excel’s graphics capabilities

      

Adding Sparklines

      The visual presentation of data is extremely important in statistics. Visual presentation enables you to discern relationships and trends you might not see if you look only at numbers. Visual presentation helps in another way: It’s valuable for presenting ideas to groups and making them understand your point of view.

      Graphs come in many varieties. In this chapter, I explore the types of graphs you use in statistics and explain when it’s advisable to use them. I also show you how to use Excel to create those graphs.

      Suppose you have to make a pitch to a Congressional committee about commercial space revenues in the early 1990s.

Industry 1990 1991 1992 1993 1994
Commercial Satellites Delivered 1,000 1,300 1,300 1,100 1,400
Satellite Services 800 1,200 1,500 1,850 2,330
Satellite Ground Equipment 860 1,300 1,400 1,600 1,970
Commercial Launches 570 380 450 465 580
Remote Sensing Data 155 190 210 250 300
Commercial R&D Infrastructure 0 0 0 30 60
Total 3,385 4,370 4,860 5,295 6,640

      Data from U.S. Department of Commerce

Snapshot shows graphing the data in Table 3-1.

      FIGURE 3-1: Graphing the data in Table 3-1.

      The graph shows you trends you might not see as quickly on the table. (Satellite services rose fastest. Commercial launches, not so much.) Bottom line: Tables are good; graphs are better.

      Graphs help bring concepts to life that might otherwise be difficult to understand. In fact, I do that throughout the book. I illustrate points by, well, illustrating points!

      First of all, Excel uses the word chart instead of graph. Like the graph, er, chart in Figure 3-1, most chart formats have a horizontal axis and a vertical axis. Several other formats (pie, treemap, and sunburst), which I show you later in this chapter, do not. Neither the radar chart nor the box-and-whisker chart (which also appear in this chapter) has a horizontal axis.

      By convention, the horizontal axis is also called the x-axis, and the vertical axis is also called the y-axis.

      Also, by convention, what goes on the horizontal axis is called the independent variable, and what goes on the vertical axis is called the dependent variable. One of Excel’s chart formats reverses that convention, and I bring that to your attention when I cover it. Just to give you a heads-up, Excel calls that reversed-axis format a bar chart. You might have seen the chart shown in Figure 3-1 referred to as a bar chart. So have I. (Actually, I’ve seen it referred to as a bar graph, but never mind that.) Excel calls Figure 3-1 a column chart, so I say columns from now on.

      Getting back to independent and dependent, these terms imply that changes in the vertical direction depend (at least partly) on changes in the horizontal direction.

      Another fundamental principle of creating a chart: Don’t wear out the viewer’s eyes! If you put too much into a chart in the way of information or special effects, you defeat the whole purpose of the chart.

      For example, in Figure 3-1, I had to make some choices about filling in the columns. Color coded columns would have been helpful, but the page you’re looking at shows only black, white, and shades of gray.

      A lot of chart creation skill comes with experience, and you just have to use your judgment. In this case, my judgment came into play with the horizontal gridlines. In most charts, I prefer not to have them. Here, they seem to add structure and help the viewer figure out the dollar value associated with each column. But then again, that’s just my opinion.


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