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Options

Worked examples

The How-To pages build this chart step by step from sample data, one walkthrough per data layout the tool accepts. Start there if you would rather see a finished result than read the settings.

The three analyses share one dialog ("Correlation"). Which statistic you get is decided by the ribbon entry you launch, not by a dialog setting:

Ribbon entry Statistic Worksheet
Pearson's Correlation (Normal) Pearson correlation matrix with p-values Correlation
Spearman's Correlation (Non-normal) Spearman rank correlation matrix with p-values SpearmanCorrelation
Covariance Covariance matrix (no p-values) Covariance

Data Tab

  • Data Types: a per-column dropdown to reclassify any column if it was detected wrong
  • Data Columns (select at least 2): the columns to correlate. Numeric columns only (Continuous, Integer, Count); all eligible columns start selected. Selecting fewer than two shows "Please select at least 2 data columns for correlation analysis."

There is no GroupBy, frequency column, or overlay option for these analyses, and no task pane afterward.

How the data is aligned

Blank and non-numeric cells are removed from each selected column first, and then every column is cut to the length of the shortest one. A blank in the middle of a column therefore shifts that column's values against the others, so the pairs no longer come from the same rows. At least two values per column are required.

Reading the output

  • With exactly two columns, a compact table shows the coefficient and its p-value. With more columns, a full matrix shows a p-value row and a coefficient row per variable, with one cell per pairing.
  • p-values at or below 0.05 are shown in bold red. Values that cannot be computed show "NA".
  • The covariance matrix includes the diagonal, which is each variable's own variance (the sheet notes this).

The formulas, including the t-test behind the p-values, are on Math Details.

See Also