## Introduction

This article describes the different methods you can use to show statistical significance in Q. Where a result is computed as being statistically significant it can be presented in a variety of ways.

## Method

### Changing the Tests on Tables and Charts

The way that tests are shown on tables and charts is determined by the selection in the **Show significance** drop-down menu at the top-middle of the **Outputs** tab: .

When set to **No**, no significance is shown. When set to **Compare columns**, column comparisons, or *pairwise tests *are used. By default **Arrows and Font Colors, **or *exception tests*, are used. This is the same as **Arrows** and **Font Colors** separately. This setting can be changed for an entire project in the **Statistical Assumptions** menu, and for all future projects using Project Templates.

### Arrows

On a standard crosstab, arrows represent the results of Testing the Complement of a Cell. NOTE: Starting in Q 5.14 and onward, this type of significance testing is called *Exception tests.* For discussions of the interpretations of tests on different types of tables, see Reading Tables and Interpreting Significance Tests.

Arrows point up when a result is significantly higher and down if significantly lower. The length of the arrows relates to the degree of statistical significance, as determined by the Corrected p statistic. The specific relationship between the length of arrows and significance is governed by the settings in the **Statistical Assumptions** menu table of settings called **Significance levels and appearance**.

### Font Color (and Column and Line Color)

In tables and most charts, significant results are color-coded (by default, blue and red; e.g., ). The testing is conducted in the same way as with Arrows, except that a higher result is by default shown in blue and lower in red.

When using **Time Series** charts, the lines and bars are color-coded to indicate significance if the **Font Color** option is selected.

### Arrows and Font Colors (default)

Both arrows and colors are used. See the two sections above for details.

### Compare columns

Letters or other codes are used to indicate significant differences between results in different columns. Alternatively, these can be manually selected by right-clicking on the table and selecting **Statistics - Cells** **> Column Comparisons **and** Statistics - Below >** **Column Names**.

Q uses Corrected p when determining whether to assign letter or not, and when determining which symbols to apply (e.g., UPPERCASE or lowercase).

Settings regarding the symbols to be shown are in the **Statistical Assumptions** sections on **Significance levels and appearance **and **Column comparisons**.

## Other ways of showing statistical significance

### Table names

Where Smart Tables is used, tables are classified as being `Significant` and `Insignificant` in the **Report **Tree, with the p-Values shown in the names of the tables.

### Reports from planned tests

Significance tests can be conducted by selecting cells and pressing . See How to Do Planned Tests of Statistical Significance.

### Multivariate outputs

Regression and Segments analyses of **Experiment **and **Ranking **questions contain statistical tests of the parameters in their outputs.

### Cell shading and other tools

Custom ways of showing statistical significance can be created using Rules (see How to Use Rules in Q to get started). One example is Significance Testing in Tables - Color Significant Cells. See How to Modify Significance Tests Using Rules for more information.

## Next

How to Change Q's Default Statistical Assumptions When Setting Up Projects

How to Interpret "Inconsistent" Statistical Testing Results

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