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:
- With Respect to the Total Sample
- 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.
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.