Data Mining Module Five Exercise 5 Guidelines and Rubric />OverviewJMP (pronounced jump) is a powerful and interactive data visualization and statistical analysis tool.

Example: Big Class.jmp (Help > Sample Data) Simple Linear Regression Simple linear regression is used to model the relationship between two continuous variables. Simple Linear Regression Using Fit Y by X 1. From an open JMP® data table, select Analyze > Fit Y by X. 2. Click on a continuous variable from Select Columns, and click Y, Response (continuous variables have blue triangles). 3. Select a second continuous variable, and click X, Factor. 4. Click OK to generate a scatterplot. 5. To fit a regression line, click on the red triangle and select Fit Line. By default, JMP will provide the following results: • The regression equation (under Linear Fit). • The Summary of Fit. • Lack of Fit (if the data table includes replicates of X values). • The ANOVA table. • The parameter estimates. Additional options, such as residual plots and confidence curves, are available from the red triangle next to Linear Fit (directly under the graph). Tips: • For other fit options, such as polynomial, transformation (fit special) and spline, use the top red triangle. • To add a legend, change markers, or make other changes to the graphical display, right-click on the graph. • To fit separate lines for categories of a grouping variable, click on the top red triangle, select Group By, and choose a grouping variable. Then, click on the top red triangle and select Fit Line. JMP will fit separate lines and provide results for each level of the grouping variable. Notes: Simple linear regression can also be performed from Analyze > Fit Model. For more details on regression analysis, see the book Basic Analysis (under Help > Books) or search for “regression” in the JMP Help. jmp.com/learn rev 02/2014

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