When the population means are equal, the estimated standard error for the independent-measures t test provides a measure of how much difference to expect between two sample means. For each of the...

Extracted text: When the population means are equal, the estimated standard error for the independent-measures t test provides a measure of how much difference to expect between two sample means. For each of the following situations, assume that Pi = P2 and calculate how much difference should be expected between the two sample means. (Use one decimal place.) One sample has n = 6 scores with SS 70, and the second sample has n = 10 scores with SS = 140. One sample has n = 6 scores with SS = 310, and the second sample has n = 10 scores with SS = 530. %3D In the second part of this question, the samples have larger variability (bigger SS values) than in the first part, but the sample sizes are unchanged. How does larger variability affect the size of the standard error for the sample mear difference? Larger variability has no effect on standard error. Larger variability produces a larger standard error. Larger variability produces a smaller standard error.