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Scatter icon_scatter_2d

Scatter icon_scatter_2d

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Scatter icon_scatter_2d

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In the Scatter tab, view all input variable and output response data in a scatter plot and correlation map.

hmtoggle_plus1greyScatter Plots

Scatter plots illustrate the dependency between a random input variable and an output response or between an output response and an output response.

Use the Channel selector to select input variable and/or output response data to plot along the X and Y axes. You can select multiple input variables and/or output responses for the Y Axis.

setup__post_process_scatter2d

 
hmtoggle_plus1greyCorrelation Map

A correlation map displays correlation values.

Select one or more cells in the map to display a scatter plot of the selected correlation values.

Correlation measures the strength and direction between associated variables. Correlation coefficients can have a value from -1 to 1; -1 indicates a strong but negative correlation and 1 indicates a strong and positive correlation. In the image below, correlations of 0.85, 0.01, 0.34 and -0.71 are plotted.

setup_post_process_scatte2d2

The Pearson product-moment correlation assumes a linear association, and the coefficient values indicate how far away all of the data points are from a line of best fit through the data. The Spearman's rank correlation coefficient assumes a monotonic association, and the coefficient values indicate the degree of similarity between rankings.

In the data sets below, the Pearson and Spearman's correlation coefficients are given.

-12.00000

1.0000000

10.000000

800.00000

40.000000

1200.0000

1000.0000

2000.0000

 

In the image below, Pearson's correlation coefficient is 0.82, as there is a correlation but it is not perfectly linear. Spearman's correlation coefficient is 1.0, as it is perfectly monotonic

cor_1

Pearson's product-moment correlation coefficient

cor_2

Spearman's rank correlation coefficient

 

Correlation Map Settings

Access settings for the Correlation map from the menu that displays when you click icon_burger_button (located above the map).

1.Pearson product-moment / Spearman's rank. By default, the correlation coefficient values are set to Pearson product-moment correlation, but the correlation coefficient values can be changed to Spearman's rank correlation coefficient.
2.Correlations ≥ 0.00. Shows only the column/rows with cells over the specified threshold.
3.Show Variables & Responses. Restricts the view of the entire correlation matrix to input variables only, output responses only, input variables and output responses, or input variables versus output responses.
4.X-Bounds / Y-Bounds. Displays the X and/or Y Bounds in the scatter plot.

tab_scatter_2d_correlation_map