BUEC 232 Lecture Notes - Lecture 10: Binomial Theorem, Binomial Distribution, Statistic

• School: Simon Fraser University
• Department: Business Economics
• Course: BUEC 232
• Professor: N. Payne

Document Summary

The distribution of a sample statistic: sample mean: take random sample of students and compute average gpa in sample, sample count: ask 20 people whether or not they will vote republican party. Important sampling distributions: sample average, sample count: number of successes in sample, sample proportion: proportion of successes in sample. Binomial setting for sample counts and proportions: fixed number of observations, n, only two outcomes for each observation: success or failure, observations are independent, probability of success is the same for each trial, p. Binomial distribution: let x be the number of successes in a binomial setting, the probability distribution of x is called the binomial distribution with parameters n and p. Binomial formula: if x has the binomial distribution with n observations and probability p of success on each observation, the possible values of x are 0,1,2, n. If k is any one of these values: some examples include: loaded coins being tossed.