How to Show Grouping in Scatterplots using Statistica Written by Dell Software Introduction A scatterplot shows the relationship between continuous variables. Showing a grouping factor in the plot adds another dimension and can greatly enhance a plot s usefulness. This technical brief explores two ways of showing a grouping variable in a scatterplot using Dell Statistica, an analytics software package that offers data preparation, statistics, data mining and predictive analytics, machine learning, model deployment and reporting. The difference between the two methods is the fit line: One method uses one fit line for all levels of a grouping factor, but shows the levels with point marker colors and patterns. The other method fits separate lines for each group. Option 1: Using one fit line for all groups Opening the sample data set The data set used in this example, Irisdat.sta, contains measurements for various parts of the flower for three different varieties of iris. To open the data set, select the Home tab, and in the File group, click the Open arrow. From the menu, select Open Examples to display the Open a Statistica Data File dialog box. Double-click the Datasets folder, and then open Irisdat.sta. Step 1: Select the variables for the scatterplot. Select the Graphs tab. In the Common group, click Scatterplot to display the 2D Scatterplots startup panel. Click the Variables button to display the Select Variables for Scatterplots dialog box, and select SEPALLEN as X and SEPALWID as Y, as shown in Figure 1. Then click the OK button. Step 2: Create the subsets for the grouping factor. On the Advanced tab of the 2D Scatterplots startup panel, click the Mark Selected Subsets button, as shown in Figure 2. The Specify Multiple Subsets dialog box will be displayed. Create three subsets for the grouping factor IRISTYPE, as shown in Figure 3. Click OK in the Specify Multiple Subsets
A scatterplot shows the relationship between continuous variables. Showing a grouping factor in the plot adds another dimension and can greatly enhance a plot s usefulness. Figure 1. Selecting the variables for the scatterplot dialog box, and then click OK in the 2D Scatterplots startup panel. The resulting scatterplot The resulting graph is a scatterplot that contains one fit line for all points and that distinguishes points by the grouping variable IRISTYPE with colors and point markers (see Figure 4). Option 2: Using separate fit lines for the groups Statistica also enables you to use separate fit lines for the groups in your scatterplot. To do this, create a categorized graph. Step 1: Select the variables for the scatterplot. Figure 2. The 2D Scatterplots startup panel 2
Start a new 2D Scatterplots analysis, and select variables as shown in Figure 1. Step 2: Select the categorization variable. In the 2D Scatterplots startup panel (shown in Figure 2), select the Categorized tab. In the X-Categories group box, select the On check box. The options will become active. Click the Change Variable button to display the Select Categorization Variable dialog box, as shown in Figure 5. Select IRISTYPE. Then click OK to close this dialog box and return to the 2D Scatterplots startup panel. Figure 3. Creating three subsets for the grouping factor, IRISTYPE One method for showing grouping uses one fit line for all levels of a grouping factor, but shows the levels with point marker colors and patterns. Figure 4. A scatterplot that contains one fit line for all points and that distinguishes points by the grouping variable IRISTYPE with colors and point markers 3
Step 3: Specify the layout. Statistica provides a number of options (Integer mode, Unique values, Categories and so on) to give you flexibility with the grouping variable. A categorization variable does not have to be categorical in nature. The resulting graph is a scatterplot that contains one fit line for all points, but distinguishes points by the grouping variable IRISTYPE with colors and point markers. In the Layout group box, select the Overlaid option button, as shown in Figure 6. Then click OK to create the graph. The resulting scatterplot In the resulting scatterplot, three separate fit lines are shown for the three categories, in addition to the groups being designated by colors and point markers (see Figure 7). Conclusion Statistica provides an intuitive, easyto-use platform designed to empower Figure 5. Selecting the categorization variable both business users and sophisticated analysts. As this technical brief demonstrates, in just two or three easy steps, you can enhance a plot s usefulness by showing a grouping factor, using either one fit line for all levels of a grouping factor or separate fit lines for each group. Figure 6. Specifying the layout for the scatterplot 4
Statistica also enables you to use separate fit lines for the groups in your scatterplot. Figure 7. A scatterplot with separate fit lines for three groups About Dell Software Dell Software helps customers unlock greater potential through the power of technology delivering scalable, affordable and simple-to-use solutions that simplify IT and mitigate risk. The Dell Software portfolio addresses five key areas of customer needs: data center and cloud management, information management, mobile workforce management, security and data protection. This software, when combined with Dell hardware and services, drives unmatched efficiency and productivity to accelerate business results. www.dellsoftware.com. 5
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