Download presentation

Presentation is loading. Please wait.

Published byAlysa Essex Modified over 2 years ago

1
Sampling Probability Sampling Nonprobability Sampling

2
Probability Sampling Sampling element Population Target population Sampling frame Sampling ratio

3
There is a classic Jimmy Stewart movie, Magic Town, about "Grandview," a small town in the Midwest that is a perfect statistical microcosm of the United States, a place where the citizens' opinions match perfectly with Gallup polls of the entire nation. A pollster (Jimmy Stewart), secretly uses surveys from this "mathematical miracle" as a shortcut to predicting public opinion. Instead of collecting a national sample, he can more quickly and cheaply collect surveys from this single small town. The character played by Jane Wyman, a newspaper editor, finds out what is going on and publishes her discovery. As a result the national media descend upon the town, which becomes, overnight, "the public opinion capital of the U.S."

4
Probability Sampling

5
Sampling Distribution

6
Probability Sampling Random sample Sampling error Four Ways to Sample Randomly – Simple Random – Systematic – Stratified Sampling – Cluster Sampling

7
Random Sample Sampling Error: Variation Component Sample size Component

9
R Session data=c(1,1,0,0,0,0,1,1,0,1,1,0,1,1,1,0) population.mean=mean(data) #samples of size 5 a.sample=sample(x=data,size=5,replace=FALSE) a.mean=mean(a.sample) #another sample b.sample=sample(data,5,FALSE) b.mean=mean(b.sample) #Distribution of sample mean #We need to sample lots of times sim.runs=100 mean.sample=NA for (i in 1:sim.runs){ sample.data=sample(data,5,FALSE) mean.sample[i]=mean(sample.data) } hist(mean.sample,breaks=4)

10
Sampling Distribution and Sampling Error

12
Sampling and Confidence x

13
Important Concepts in Sampling Margin of Error Finite Population Correction Factor Sampling error Next: Sample size

15
Other Probability Sampling Designs

Similar presentations

© 2017 SlidePlayer.com Inc.

All rights reserved.

Ads by Google