Final answer:
N squared is a less biased estimator of magnitude of effect than w squared.
Step-by-step explanation:
The statement is true. N squared is a less biased estimator of magnitude of effect than w squared.
When comparing the two estimators, N squared refers to the effect size estimate using the sample sizes (n) of each group, while w squared refers to the effect size estimate using the sample variances (s) of each group.
Since the sample sizes (n) directly capture the size of each group, N squared provides a more accurate estimate of the effect size, while w squared may be influenced by differences in sample variances which can introduce bias.