PSY201H1 Lecture Notes - Lecture 8: A Priori Probability, Sampling Distribution, Null Hypothesis
Document Summary
Lecture 8 sampling distribution of the mean. Helps us evaluate the statistic from our sample. All possible values blah blah blah seen this slide before . Empirical approach: uses an actual or theoretical set of population scores that exist if the iv has no effect. Let"s define population of 400 unbiased coin flips: a priori probability: 50% heads. General characteristics of the sampling distribution of the mean, for any n. It"s a frequency distribution of means: those means are calculated by drawing all possible samples of n sized samples from the null population, calculating the mean for each sample, and plotting it. It contains all values the mean can take. Its mean equals the mean of the population. Its standard deviation equals the standard deviation of the raw score population, divided by the square root of the sample size: standard error of the mean . Central limit theorem: as the sample size n increases, sampling .
