STA220H1 Lecture 10: Sampling Distributions Pt. 2

• School: UTSG
• Department: Statistical Sciences
• Course: STA220H1
• Professor: Shivon Sue-Chee

Document Summary

Sampling distributions are theoretical distributions about what you believe will happen in the long run or if you increase the sample size. Is the probability distribution of the sample mean always normal with mean, and standard deviation. If population is not normal, depends on sample size, if it large enough it"ll be approximately normal (by central limit theorem) If normal, whether large or small sample size, distribution always normal. Central limit theorem: if an experiment is repeated over and over, then the. If distribution is approximately normal, probabilities for the average results, or the proportion of successes, will converge to a normal distribution. Speaks of overall shape of the distribution. The law of large numbers: as sample size increases, the sample mean will approach the expected value. Sample mean, as n increases; = population mean. How many trials are needed so that the normal distribution is a good.