Curated Help for Correlations

Curated Help feature is enabled for pivot tables in Correlations procedures.

With Curated help, the Output Viewer displays additional insights for a correlations procedure. Color-coding is used to highlight the key correlation values displayed in the Correlations table.

The feature is triggered when a table is created or modified. A color legend is displayed under the table, which helps users to interpret the overall results in the table based on correlation value indicated by colors.

Curated Help labels correlations between variables as highly positive correlation, positive correlation, no linear correlation, negative correlation, or highly negative correlation. The type of correlation in your output is marked in the color legend under the table.

This is a dynamic feature. Whenever the correlation results change, the color-coding updates automatically to reflect the new values.

The Curated Help appears beneath the Correlations table and provides summary labels for the correlation values by using color codes.

Color code

If the feature is enabled, the key correlation values in the pivot table are highlighted. The possible color code and their corresponding correlation ranges are listed in the following table:

Table 1. Color coding for Curated Help to identify correlation

Color	Value range	Type of Correlation
	Between 0.9 and 1	Highly positive
	Above 0 and below 0.9	Positive
	0	No linear correlation
	Above -0.9 and below 0	Negative correlation
	Between -1 and -0.9	Highly negative correlation

Example

The following example helps you identify a practical application of Curated Help for Pearson Correlation in your data.

Consider that a company is experiencing varied performance across departments and wants to investigate whether employee job satisfaction is related to employee productivity. Managers can use Pearson Correlation to explore the relationship between the job satisfaction and productivity of employees.

Assume that a sample of 250 employee data across 10 departments were collected. In that sample, the productivity is measured based on the number of tasks that are completed during a particular month and the job satisfaction is assessed through an internal survey.

Run the procedure for Pearson Correlation with the available data sample. Go to Analyze > Correlate > Bivariate.

If Curated Help feature is enabled, the Output Viewer highlights correlation values in the Correlations table. Under the table, the highlighted value is also labeled according to its type of correlation.

Assume that the value of Pearson Correlation between job satisfaction and productivity is calculated as 0.95. Curated Help marks this as highly positive correlation by using the corresponding color (See the table). The relationship is also denoted as Job Satisfaction <---> Productivity implying the highly positive correlation. The other categories (positive, no correlation, negative, highly negative) are marked as None, as they are not applicable in this case.

With Curated Help for Bivariate Correlation, managers can use the insights to improve the workplace practices and outcomes.