STA220H5 Lecture Notes - Lecture 7: Statistical Parameter, Central Limit Theorem, Exponential Distribution
Document Summary
Discrete random variables: a random variable takes numerical values for the random outcomes of an experiment. Formula; x = 0, , n or [ x = maximum (0, n - {n - r}), , minimum of ( n, r)] The normal distribution: z-scores, probability and areas under normal curves using tables and minitab. Chapter 6 topics: sampling distributions and their properties, estimators, the sampling distribution of 0 and the central limit theorem. A parameter is a number that describes a population. A statistic is a number that describes a sample. A sampling distribution is the probability distribution of a statistic for a sample of size n. The standard deviation of the sampling distribution of a statistic is called the standard error of the statistic. A point estimator of a population parameter is a rule or a formula that tells us how to use sample data to get a single number to estimate a parameter.
