Department

GeographyCourse Code

GGR270H1Professor

Damian DupuyStudy Guide

FinalThis

**preview**shows page 1. to view the full**4 pages of the document.**GGR 270 â Lecture 7 â October 27, 2010

Central Limit Theorem II

îThe frequency of sample means will be normally distributed

îWhen the sample size is large, the sample mean is likely to be quite close to the

population mean

îA large sample is more likely to be closer to the true population mean than a smaller

sample

Variability

îStandard deviation of the sampling distribution is equal to the sample standard

deviation divided by the square root of the sample size

îThis is called the standard error of the mean

oIndicates how much a typical sample mean is likely to differ from the true

population mean

oMeasures the amount of sampling error

oThe larger the sample size (n), the smaller the amount of sampling error

How large is large

îIf sampled population is normal, then sampling distribution of means will also be

normal, no matter what the sample size

îIf the sampled population is approximately normal, then the sampling distribution of

means will be approximately normal for relatively small sample sizes

îWhen the population is skewed, the sample size must be large (n>30) before the

sampling distribution will become normal

Sample Estimation

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