not have to know all the statistical terms or assumptions in order to access them.
| Note |
| JMP’s Analyze menu contains terms such as Distribution and Fit Y by X that might be unfamiliar, but the ideas behind them are very straightforward. We describe them in simple terms as needed throughout the book. Many items under the Analyze and Graph menus are referred to as platforms or commands through this book. For example, Distribution and Fit Y by X are referred to as platforms. |
1.4 Elements of Using JMP
Before we launch JMP for the first time, let’s look at the four common elements of a JMP analysis. All JMP analyses contain these elements, and they follow a consistent process.
1. The first is the JMP Home Window, where you begin a JMP session (Figure 1.19). This is your mission control center. As described earlier in this chapter, from here you can open or create a data table or easily navigate between data tables, results, and help.
Figure 1.19 The JMP Home Window
2. The second element is a Data Table where your data reside, which you might have imported or opened through the Home Window (Figure 1.20). The data table is also where you will usually initiate an analysis or graph described next. We will cover the Data Table in Chapter 2.
Figure 1.20 A JMP Data Table
3. Once you have a data table open in JMP, you will want to select a task through the JMP menus. These tasks (or commands as we call them in JMP) generate a Launch Window to execute your desired command (Figure 1.21). You will notice that the columns or variables from your data table are pre-populated in the launch window. Chapters 3 through 6 will explore these tasks and their results.
Figure 1.21 A JMP Launch Window
4. The result of any executed command is called the Report Window, which contains the graphs and statistics that you have asked JMP to glean from your data (Figure 1.22). We will be seeing Report Windows throughout this book as we illustrate JMP’s features, but Chapter 7 will focus on how to share these graphs and reports with others.
Figure 1.22 A Report Window
1.5 JMP Launch Dialog Windows
Throughout this book, each set of instructions used to create a graph or an analysis is prompted by a launch window that follows a consistent format and execution. To launch a window, however, you must first open a data table.
For purposes of illustration, we will open the Equity.jmp data table:
1. Select Help Sample Data Library Equity.jmp.
2. Select Analyze Distribution (see Figure 1.23).
Figure 1.23 Selecting the Distribution Platform
3. This generates the Distribution window with the columns (variables) from the Equity.jmp data table populated in the Select Columns list (see Figure 1.24).
Figure 1.24 The Distribution Launch Window
Most JMP launch windows consist of three main elements, organized from left to right (see Figure 1.25):
Figure 1.25 Launch Window Basics
• Available columns (or variables) of data to analyze from your data table. These appear on the left under Select Columns.
• Roles that you want to place (or cast) on the column(s). In this area, you see buttons and empty areas under Cast Selected Columns into Roles. Within these empty areas, you are given a hint in italics about which columns are required and which are optional to run the analysis.
• Action buttons to execute commands.
To use this Distribution window or almost any other in JMP, click on a column and select the role (or click and drag the column into that role’s empty space). Once you are satisfied with your selections, select OK.
Almost every analysis and graph window in JMP appears in this way. Now that you have learned this format, you are ready to handle just about any command window in JMP.
| Note |
| The Y, Columns role refers to what column you want to place on the vertical, or y, axis. In other windows, such as Fit Y by X, you also have an X role to select that corresponds to the horizontal, or x, axis. The Weight, Freq, and By roles are more specialized, but can streamline your analyses often without the requirement of reshaping your data (For more information, see Help JMP Documentation Library Using JMP Get Started Launch Windows). |
1.6 The Excel Add-In (Optional)
We find that many new users of JMP are often Microsoft Excel users too. JMP can easily import Excel data, which we will describe in greater detail in Chapter 2, but one feature that Excel power users might appreciate is the JMP add-in for Excel. The Excel add-in is a convenient Windows-only way to launch JMP platforms from within the Excel environment. If Excel is installed on your Windows computer and you then install JMP, the add-in should appear as a new tab along the top of your Excel window. (See Figure 1.26.) If it does not, go to “Add-ins” within Excel and select the check box next to the JMP add-in item.
Figure 1.26 The JMP Add-In Tab in Excel
Selecting the JMP tab will reveal a JMP ribbon providing a good selection (but not all) of the commonly used JMP platforms (see Figure 1.27).
Figure 1.27 The JMP Ribbon in Excel
Because the JMP environment offers dynamic and visual exploration of your data, each JMP platform option will launch JMP, convert your Excel worksheet into a JMP data table, and set up the corresponding launch window within the JMP environment. Let’s briefly summarize their functions.
1. Preferences helps bring your data to JMP in the right format. Here, you can specify the number of header rows in your Excel worksheet and whether to bring over hidden rows or columns.
2. Data Table automatically converts your Excel worksheet into a JMP Data Table. Note that it will use the preferences that you have set. If your data does not transfer correctly, change your preferences accordingly or use the Excel Import Wizard discussed in Chapter 2.
3. Graph Builder is an easy-to-use data visualization platform. Selecting this option will convert your worksheet into a JMP data table, launch the Graph Builder platform, and populate the dialog box with your variables or columns so that you are ready to visualize your data.
4. Distribution, Fit Y by X, Fit Model, Time Series, and Control Chart will convert your worksheet into a JMP data table and launch the corresponding platform with your variables ready to be assigned into roles.
5. Create/Edit Model and Run Model enable you to visualize your spreadsheet models using JMP’s profiler. If you are interested in performing “what-if” analysis on your spreadsheet models, the profiler enables you to do so visually. This is a great tool for presenting models because you can