PSY 2174 Lecture Notes - Lecture 9: Central Limit Theorem, Sampling Distribution, Sampling Error

• School: University of Ottawa
• Department: Psychology
• Course: PSY 2174
• Professor: Heather Poole

Document Summary

But it is not really a problem since we are drawing from large populations. Remember, we use samples to estimate populations. Populations distribution: distribution of individual scores (n=1) Sampling distribution of the mean: distribution of sample means (n>1) Standard deviation of this distribution is called standard error. Comparing an individual of 1 compared to the whole population. Don"t want to compare a group of average scores to a population of individual scores. Sampling distribution of the mean is crucial concept in statistics. Variability of statistic t from sample to sample due to change. For example we know our population distribution of iq score is nd (100, 15) But each sample of people we may take won"t have exactly a mean of 100 it may be 102, 96, 5 etc. Thus, any sample statistic value will be error prone" (different from the true population mean)