PS296 Chapter Notes - Chapter 13: Null Hypothesis, Standard Deviation, Variance
Student's t Applied to Difference Scores
Difference/gain scores:
-the set of scores representing the difference between the subjects performance on two
occasions
-change in a person's score from the pretest measure to the posttest measure
-if we think of our data as being the set of difference scores, the null hypothesis that the mean
of a population of difference scores (μD) equals 0
H0: μD = μA – μB = 0
-now we are testing a hypothesis using one sample of data (difference scores)
-the data are different scores
-the mean and the standard deviation are based on differences
-t was defined as the difference between a sample mean and a population mean, divided by the
standard error of the mean
-D̄ / Dbar represents the sample of difference scores
t = D̄ - 0
SD/√N
-D̄ is the mean
Document Summary
The set of scores representing the difference between the subjects performance on two occasions. Change in a person"s score from the pretest measure to the posttest measure. If we think of our data as being the set of difference scores, the null hypothesis that the mean of a population of difference scores ( d) equals 0. H0: d = a b = 0. Now we are testing a hypothesis using one sample of data (difference scores) The mean and the standard deviation are based on differences. T was defined as the difference between a sample mean and a population mean, divided by the standard error of the mean. D / dbar represents the sample of difference scores t = d - 0. Sd is the standard deviation of the difference scores. Degrees of freedom for the matched-sample case are the same as for the one-sample scale. N will be equivalent to the number of differences.
