ECON 307 Lecture Notes - Lecture 3: Central Limit Theorem, Null Hypothesis, Statistical Inference
Document Summary
Descriptive statistics- used to describe the distribution of a variable in a sample. Inferential statistics- use information from a sample to find out what might be true about entire pop. Sample- part of population for which we observe data. Statistic- observable # calculated from a sample describe characteristics of data in a sample. Parameters- unobservable numbers that describe characteristics of the entire population. Sampling distribution- shows what kind of values a sample statistic can take on and how often it takes on those values. Tells us what kind of estimates we should expect to get from the sample and how the estimates are distributed. Central limit theorem- draw a random sample from any pop w mean and standard deviation. If it is large enough, then the sampling dist. Of the sample mean is normal w mean and standard deviation = [pop st. dev / sqrt(n)]
