Session 12

# How to Interpret Significant Differences

## Understanding Significant Differences

What Are They?

Significant differences are calculations applied to the percentages or means in the results tables. A difference is considered statistically significant when it goes beyond what would be expected by chance alone.

In your project’s results tables, you will encounter significant differences in two key contexts:

1. With Respect to the Total Sample
2. Between Sub-Samples or Analyzed Groups

Let’s begin by exploring significant differences concerning the total sample. ## Significant Differences with Respect to the Total

Identifying Signs and Meaning

In results tables, significant differences concerning the total sample are indicated by plus (+) and minus (-) signs.

• Plus (+) Sign: This sign suggests that the difference is higher than the total. In other words, it signifies an increase above the expected values.
• Minus (-) Sign: This sign implies that the difference is lower than the total. It represents a decrease compared to the expected values.

Let’s illustrate this concept with an example: ## Interpreting the Example

A Visual Explanation

In the example above, you can observe the following:

• Total (%): Represents the overall percentage for a specific response.
• Sub-Group 1 (%): Shows the percentage for that response within Sub-Group 1.
• Sub-Group 2 (%): Displays the percentage for that response within Sub-Group 2.

The plus (+) and minus (-) signs indicate the direction of the significant difference:

• +: The percentage in Sub-Group 1 is higher than the total percentage.
• -: The percentage in Sub-Group 2 is lower than the total percentage.

## Conclusion

Understanding and interpreting significant differences is crucial in extracting valuable insights from your research data. In our next session, we’ll explore methods to draw meaningful conclusions from these differences.