The p (probability) value is the basis for deciding whether or not there is a relationship between the data being tested. Generally you start with the null hypothesis, which is the assumption that there is no relationship between the data. If the p value is small enough (usually less than 0.05 or 0.01), you can reject the assumption of no relationship and conclude that there is a relationship.

A full list of the p values for each pair of columns tested in each row is available in the diagnostics information file for the table. UNICOM Intelligence Reporter reports p values as a decimal value with six decimal places (although trailing zeroes after the decimal symbol are not displayed by default when you open the file in Microsoft Excel). A reported p value of 0.05 is equal to a significance level of 5%. If the p value is smaller than the significance level you select for the test, the test statistic is significant.

The p value is also called the observed significance level.

This example shows the p values for the first column proportions test example. It shows the row/cols and pval columns from the diagnostics data with the addition of the row labels. In the example, the column proportions test was run at the 5% significance level, and one row, Human biology, was found to be significant. Notice that the p value in this row is 0.009396. This is the only row with a p value of less than 0.05.

A full list of the p values for each pair of columns tested in each row is available in the diagnostics information file for the table. See Diagnostics information for further details.