What Statistical Value Indicates Significance Between Means?

Brian is trying to determine if there's a significant difference between the means in his study. To find his answer, he needs to look at the p-score.

Here's why:

• p-score: This value indicates the probability of observing the results obtained (or more extreme results) if there is no real difference between the means. A small p-score (typically less than 0.05) suggests that the observed difference is unlikely to be due to random chance, indicating a statistically significant difference.

Let's consider the other options:

• ANOVA score: ANOVA (Analysis of Variance) is a statistical test used to compare means from multiple groups. While it's relevant to Brian's goal, the 'ANOVA score' itself doesn't directly pinpoint significance.* Eigenvalues: Eigenvalues are associated with factor analysis and principal component analysis, not directly with determining significant differences between means.* F-Ratio: The F-ratio is a component of ANOVA. It represents the ratio of variance between groups to variance within groups. However, it's the p-score derived from the F-ratio that ultimately determines significance.

In conclusion, Brian should focus on the p-score to determine if the difference between the means in his study is statistically significant.