Table 5.
Study 1. Rotated principal-component matrix: New measures plus college-admissions tests (g-based) a.
| Component | ||
|---|---|---|
| 1 | 2 | |
| Hypotheses (New) | 0.68 | −0.11 |
| Experiments (New) | 0.82 | 0.32 |
| Conclusions (New) | 0.74 | −0.13 |
| SAT Reading | −0.11 | 0.83 |
| SAT Math | 0.24 | 0.71 |
| ACT | −0.48 | 0.66 |
| Extraction Method: Principal Component Analysis. | ||
| Rotation Method: Varimax with Kaiser Normalization. | ||
| a Rotation converged in 3 iterations. | ||
Notes: Two principal components had Eigenvalues greater than 1. Component 1 had an Eigenvalue of 2.06, accounting for 34.3% of the variance in the data. Component 2 had an Eigenvalue of 1.68, accounting for 28.0% of the variance in the data. Cumulative percent variance accounted for was 62%.