PSY 2106 Lecture 5: Probability and Samples

• School: University of Ottawa
• Department: Psychology
• Course: PSY 2106
• Professor: Brenda Baird

Document Summary

Select 2 random scores on a test and get the mean. Do this for 100 persons (so 50 different means) Each m will probably be different than the true class average (population ) because samples vary. This discrepancy between the sample and the population is called the sampling error: example: frequency distribution histogram for a population of four scores: 2, 4, 6, 8; = 5. All the possible samples of n = 2 scores that can be obtained from the population presented. The distribution of all 16 sample means for n = 2. The distribution shows the 16 possible sample means. Distribution is now means, not individual scores. Contains all possible sample means of the same size with a central m (m of the distribution of sample means), so it is a sampling distribution. Each sample m varies about the mean of the sampling distribution. This variability is called the standard error.