STAB22H3 Lecture Notes - Lecture 10: Central Limit Theorem, Statistical Hypothesis Testing, Confidence Interval

• School: UTSC
• Department: Statistics
• Course: STAB22H3
• Professor: Asal Aslemand

Document Summary

Draw a srs of size n from a large population having population p of success. Let x be the count of success in the sample and p x n the sample proportion of successes. When n is large, the sampling distributions of these statistics are approximately normal: Assumptions and conditions: randomization condition: the sample should be a simple random sample of the population. 10% condition: if sampling has not been made with replacement, then the sample size, n, must be no larger than. Success/failure condition: the sample size has to be big enough so that both np and nq are greater than 10. If a population has the n( , ), then the sample mean. X of n independent observations has the n( , / n ) Draw a srs of size n from a population with mean and std dev. When n is large, sampling distribution of a sample mean x is approximately normal with mean and std dev.