Pearson Correlation Matrix
| Variables | Study Time | GPA | AI Use Frequency | Writing Confidence |
|---|---|---|---|---|
| Study Time | 1.00 | .62** | .34* | .18 |
| GPA | .62** | 1.00 | .2... |
Pearson Correlation Matrix
| Variables | Study Time | GPA | AI Use Frequency | Writing Confidence |
|---|---|---|---|---|
| Study Time | 1.00 | .62** | .34* | .18 |
| GPA | .62** | 1.00 | .28 | .41* |
| AI Use Frequency | .34* | .28 | 1.00 | .12 |
| Writing Confidence | .18 | .41* | .12 | 1.00 |
p < .05, p < .01
Interpretation
After examining the correlation matrix, I identified one strong, one moderate, and one weak relationship.
Strong correlation
There is a strong positive correlation between study time and GPA (r = .62). This means that students who spend more time studying tend to have higher GPAs. In simple terms, as study time increases, academic performance also tends to improve.
Moderate correlation
A moderate positive correlation is found between GPA and writing confidence (r = .41). This suggests that students with higher GPAs are somewhat more likely to feel confident in their writing ability.
Weak correlation
There is a weak positive correlation between study time and writing confidence (r = .18). This indicates only a slight relationship, meaning that studying more does not strongly relate to feeling more confident in writing.
One surprising finding is the weak relationship between AI use frequency and GPA (r = .28), which is lower than expected. I initially thought frequent use of AI tools such as ChatGPT would show a stronger relationship with academic performance.
Another interesting point is that the correlation between AI use frequency and writing confidence (r = .12) is very weak and may not be statistically significant. This suggests that using AI tools more often does not necessarily make students feel much more confident in their writing.
Reply to a classmate (sample)
I found your correlation matrix very interesting, especially the strong relationship between study habits and GPA. One question I have is whether you checked the significance levels for the weaker correlations, since some of them may not be meaningful statistically.