OMIS 2010 Chapter Notes - Chapter 09: Sampling Distribution, Binomial Distribution, Random Variable

• School: York University
• Department: Operations Management and Information System
• Course: OMIS 2010
• Professor: Alan Marshall

Document Summary

This chapter connects the material in chapters 4 through 8 (numerical descriptive statistics, sampling, and probability distributions, in particular) with statistical inference, which is introduced in. The most important thing to learn from this section is that if we repeatedly draw samples from any population, the values of x calculated in each sample will vary. This new random variable created by sampling will have three important characteristics: x is approximately normally: the mean of x will equal the mean of the original random variable. That is, x = x : the variance of x will equal the variance of the original random variable divided by n. that is, The sampling distribution of x allows us to make probability statements about x based on knowing the values of the sample size n and the population parameters and 2 . A random variable possesses the following probability distribution: x.