Use Binned Scatterplot to investigate the relationship between a pair of continuous variables when the dataset contains many observations.

For information about data considerations, examples, and interpretation, go to Overview for Binned Scatterplot.

Variables

You can graph the x and y-variables as individual pairs or you can graph every combination of the x-y variables. The y-variable is the variable that you want to explain or predict. The x-variable is a corresponding variable that might explain or predict changes in the y-variable. All columns must be numeric, and each x-y variable pair must have the same number of rows.

First, choose one of the following options.

Each Y versus each X
Select to display a separate graph for each possible combination of x and y-variables that you enter.
XY Pairs
Select to display a separate graph for each pair of x and y-variables that you enter.

Then, enter the variables.

Y variables
Select the variables that you want to explain or predict.
X variables
Select the variables that might explain or predict the changes in the Y variables.

Gradient defined by mean

Select to define the gradient scale by the value of a third variable.

By variables

Enter one or more grouping variables in By variables to create a separate binned scatterplot for each level of the grouping variables. The columns that you enter can be numeric or text, and must be the same length as the columns in Y variables and X variables. The y-scales for each variable are the same across the multiple binned scatterplots.
Show all combinations

When you enter multiple By variables, Minitab enables the Show all combinations checkbox. Select this option to create a separate binned scatterplot for each combination of groups created by the By variables. If you do not select this option, Minitab creates a plot for each group of each By variable.

For example, the first By variable has 2 groups, Male and Female, and the second By variable has 2 groups, Employed and Unemployed. If you select Show all combinations, Minitab creates 4 separate plots for the combinations of Male/Employed, Male/Unemployed, Female/Employed, and Female/Unemployed. If you do not select Show all combinations, Minitab creates 4 separate plots for Male, Female, Employed, and Unemployed.

Gradient type

Select the color scale for the bins.

Diverging
Bins with high values are red, and bins with low values are blue. In Gradient symmetric around value, enter a value to center the gradient scale at a specific value rather than the center of the frequency of the binned data.
Sequential from low to high
Bins with high values are dark blue, and bins with low values are light blue and light gray. You can use this option to highlight bins with more productivity or to maximize revenue.
Sequential from high to low
Bins with low values are dark blue, and bins with high values are light blue and light gray. You can use this option to highlight bins with low defect rates or to minimize cost.

Scale

Use the same scale across multiple graphs. These options are available only when you enter more than one pair of columns in X variables and Y variables and the layout is set to display separate graphs for each XY pair.

Same Y-scale
Use the same Y-scale across all graphs.
Same X-scale
Use the same X-scale across all graphs.
Same gradient scale
Use the same color gradient scale across all graphs. For the same pair of x y-variables, the gradient scale will always be the same.

Log Transformation

A logarithmic scale linearizes logarithmic relationships by changing the axis, so that the same distance represents different changes in value across the scale. For example, in the scatterplot with the untransformed x-scale, the function y = log(x) is not linear. When you transform the x-scale to logarithm base 10, the form of the data is linear. These options are only available for positive data.
Log transformation: Y-scale
Select to transform the Y-scale using logarithm base 10.
Log transformation: X-scale
Select to transform the X-scale using logarithm base 10.
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