Automatically Update Analyses and Graphs
When you make a change to a data table, you can use the Automatic Recalc feature to automatically update analyses and graphs that are associated with the data table. For example, if you exclude, include, or delete values in the data table, that change is instantly reflected in the associated analyses or graphs. Note the following information:
• Some platforms do not support Automatic Recalc. For more information, see the JMP Reports chapter in the Using JMP book.
• For the supported platforms in the Analyze menu, Automatic Recalc is turned off by default. However, for the supported platforms in the Quality and Process menu, Automatic Recalc is turned on by default, except for the Variability/Attribute Gauge Chart, Capability, and Control Chart.
• For the supported platforms in the Graph menu, Automatic Recalc is turned on by default.
Example of Using Automatic Recalc
This example uses the Companies.jmp sample data table, which contains financial data for 32 companies from the pharmaceutical and computer industries.
1. Select Help > Sample Data Library and open Companies.jmp.
2. Select Analyze > Fit Y by X.
3. Select Sales ($M) and click Y, Response.
4. Select # Employ and click X, Factor.
5. Click OK.
Figure 8.2 Initial Scatterplot
The initial scatterplot shows that one company has significantly more employees and sales than the other companies. You decide that this company is an outlier, and you want to exclude that point. Before you exclude the point, turn on Automatic Recalc so that your scatterplot is updated automatically when you make the change.
6. Turn on Automatic Recalc by selecting Redo > Automatic Recalc from the red triangle menu.
7. Click on the outlier to select it.
8. Select Rows > Exclude/Unexclude. The point is excluded from the analysis and the scatterplot is automatically updated.
Figure 8.3 Updated Scatterplot
If you fit a regression line to the data, the point in the lower right corner is an outlier, and influences the slope of the line. If you then exclude the outlier with Automatic Recalc turned on, you can see the slope of the line change.
9. Fit a regression line by selecting Fit Line from the red triangle menu. Figure 8.4 shows the regression line and analysis results added to the report window.
Figure 8.4 Regression Line and Analysis Results
10. Click on the outlier to select it.
11. Select Rows > Exclude/Unexclude. The regression line and analysis results are automatically updated, reflecting the exclusion of the point.
Tip: When you exclude a point, the analyses are recalculated without the data point, but the data point is not hidden in the scatterplot. To also hide the point in the scatterplot, select the point, and then select Rows > Hide and Exclude.
Figure 8.5 Updated Regression Line and Analysis Results
Change Preferences
You can change preferences in JMP using the Preferences window. To open the Preferences window, select File > Preferences.
Figure 8.6 Preferences Window
On the left side of the Preferences window is a list of Preference groups. On the right side of the window are all of the preferences that you can change for the selected category.
Example of Changing Preferences
Every platform report window has options that you can turn on or off. However, your changes to these options are not remembered the next time you use the platform. If you want JMP to remember your changes every time you use the platform, change those options in the Preferences window.
This example shows how to set the Distribution platform so that an Outlier Box Plot is not added to the initial report.
Create a Distribution Using the Default Preference Setting
1. Select Help > Sample Data Library and open Companies.jmp.
2. Select Analyze > Distribution.
3. Select Profits ($M) and click Y, Columns.
4. Click OK.
Figure 8.7 Distribution Report Window
The histogram is vertical, and the graphs includes an outlier box plot. To change the histogram to horizontal and remove the outlier box, select the appropriate options from the red triangle menu for Profits ($M). However, if you want those preferences to be in effect every time you use the platform, then change them in the Preferences window.
Change the Preference for the Outlier Box Plot and Run Distribution Again
1. Select File > Preferences.
2. Select Platforms from the preference group.
3. Select Distribution from the Platforms list.
4. Select the Horizontal Layout option to turn it on.
5. Deselect the Outlier Box Plot option to turn it off.
Figure 8.8 Distribution Preferences
6. Click OK.
7. Repeat the Distribution analysis. See “Create a Distribution Using the Default Preference Setting”.
The histogram is now horizontal and the outlier box plot does not appear. These preferences remain the same until you change them.
For details about all of the preferences, see the JMP Preferences chapter in the Using JMP book.
Integrate JMP and SAS
Note: You must have access to SAS, either on your local machine or on a server, to use SAS through JMP.
Using JMP, you can interact with SAS as follows:
• Write or create SAS code in JMP.
• Submit SAS code and view the results in JMP.
• Connect to a SAS Metadata Server or a SAS Server on a remote machine.
• Connect to SAS on your local machine.
• Open and browse SAS data sets.
• Retrieve and view data sets generated by SAS.
For complete details about integrating JMP and SAS, see the Import Your Data chapter in the Using JMP.
Example of Creating SAS Code
This example uses the Candy Bars.jmp sample data table, which contains nutrition data for candy bars.
1. Select Help > Sample Data Library and open Candy Bars.jmp.
2. Select Analyze > Fit Model.
3. Select Calories and click Y.
4. Select Total fat g, Carbohydrate g, and Protein g, and click Add.
5. From the red triangle menu for Model Specification, select Create SAS Job.
Figure 8.9 shows the SAS code. (Not all of the data is shown.)
Figure 8.9 SAS Code
Example of Submitting SAS Code
1. Select Help > Sample Data Library and open Candy Bars.jmp.
2. Select Analyze > Fit Model.
3. Select Calories and click Y.
4. Select Total fat g, Carbohydrate g, and Protein g, and click Add.
5. From the red triangle menu for Model Specification, select Submit to SAS.
6. In the Connect to SAS Server window (see Figure 8.10), choose a method to connect to SAS (if you are not already connected). For this example, select Connect to SAS on this machine.
Figure 8.10 Connect to SAS Server
7. Click OK.
JMP connects to SAS. SAS runs the model and sends the results back to JMP. The results can appear as SAS output, HTML, RTF, PDF, or JMP report format (you can choose the format using JMP Preferences). Figure 8.11 shows the results formatted as a JMP report. For details, see the Import Your Data chapter in the Using JMP book.
Figure 8.11 SAS Results Formatted as a JMP Report
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