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: Body Measurements.jmp (Help > Sample Data) Correlation Correlation is a measure of the linear association between two variables.

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Example: Body Measurements.jmp (Help > Sample Data) Correlation Correlation is a measure of the linear association between two variables. This page documents the two platforms in JMP® for assessing correlation. Correlation Between Two Variables 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. Click on a second continuous variable, and click X, Factor. 4. Click OK to generate a scatterplot. 5. To display the correlation, click on the red triangle and select the Density Ellipse > 0.95.  A 95% density ellipse, which graphically shows the correlation, will display on the scatterplot.  To show the correlation coefficient, click on the gray icon next to Correlation. Correlations Between Multiple Pairs of Variables 1. From an open JMP data table, select Analyze > Multivariate Methods > Multivariate. 2. Click on two or more continuous variables from Select Columns, and click Y, Columns. 3. Click OK to produce a scatterplot matrix with density ellipses and a table of correlations.  The Default estimation method allows JMP to determine the method for estimating correlations that is most appropriate for your data set. Tips:  Many additional correlation options are available under the red triangle next to Multivariate, including:  CI of Correlations.  Inverse Correlations.  Partial Correlations.  Pairwise Correlations (Pearson product-moment).  Nonparametric Correlations (including Spearman’s rho).  Scatterplot options are available under the red triangle next to Scatterplot Matrix. Notes: Density ellipses can also be generated from Graph > Scatterplot Matrix and Graph > Graph Builder. For additional information, search for “correlation” in the JMP Help. jmp.com/learn rev 07/2012

 
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