Descriptions of the Display and Control Options 

Show Points	Hides or shows the points in the scatterplot. A check mark indicates that points are shown.
Histogram Borders	Attaches histograms to the x- and y-axes of the scatterplot. A check mark indicates that histogram borders are turned on. See Histogram Borders.
Group By	Lets you select a classification (or grouping) variable. A separate analysis is computed for each level of the grouping variable, and regression curves or ellipses are overlaid on the scatterplot. See Group By.
Script	Contains options that are available to all platforms. These options enable you to redo the analysis or save the JSL commands for the analysis to a window or a file. For more information, see Using JMP.

Descriptions of the Fitting Options 

Fit Mean	Adds a horizontal line to the scatterplot that represents the mean of the Y response variable.	See Fit Mean.
Fit Line	Adds straight line fits to your scatterplot using least squares regression.	See Fit Line and Fit Polynomial.
Fit Polynomial	Fits polynomial curves of a certain degree using least squares regression.	See Fit Line and Fit Polynomial.
Fit Special	Transforms Y and X. Transformations include: log, square root, square, reciprocal, and exponential. You can also turn off center polynomials, constrain the intercept and the slope, and fit polynomial models.	See Fit Special.
Flexible	Provides options that enable you to control the smoothness of the estimated regression curve.	See Flexible.
Fit Orthogonal	Provides options for orthogonal regression fits, which are useful when X is assumed to vary. This option provides sub-options that reflect various assumptions about the variances of X and Y.	See Fit Orthogonal.
Robust	Provides options that reduce the influence of outliers in your data set on the fitted model.	See Robust.
Density Ellipse	Plots density ellipsoids for the bivariate normal distribution fit to the X and Y variables.	See Density Ellipse.
Nonpar Density	Plots density contours based on a smoothed surface. The contours describe the density of data points.	See Nonpar Density.

Category	Description	Fitting Commands
Regression Fits	Regression methods fit a curve to the observed data points. The fitting methods include least squares fits as well as spline fits, kernel smoothing, orthogonal fits, and robust fits.	Fit Mean Fit Line Fit Polynomial Fit Special Flexible Fit Orthogonal Robust
Density Estimation	Density estimation fits a bivariate distribution to the points. You can either select a bivariate normal density, characterized by elliptical contours, or a general nonparametric density.	Density Ellipse Nonpar Density