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Sampling. 12/4/2012. Readings. Chapter 8 Correlation and Linear Regression (Pollock) ( pp 199- 206) Chapter 6 Foundations of Statistical Inference (Pollock) ( pp 122-135) . Final Exam. SEC 1 December 12 th (Wednesday) 1:30 pm - 3:30 pm SEC 2 December 11 th (Tuesday)
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Sampling 12/4/2012
Readings • Chapter 8 Correlation and Linear Regression (Pollock) (pp 199- 206) • Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)
Final Exam • SEC 1 • December 12th (Wednesday) • 1:30 pm - 3:30 pm • SEC 2 • December 11th (Tuesday) • 1:30 pm - 3:30 pm
Final Paper • Due 12/7/2012 by 11:00AM- Doyle 226B • Turnitin Copy by 11:59PM on 12/7
Office Hours For the Week • When • Wednesday 8-4 • Thursday 10-12 • And by appointment
Course Learning Objectives • Students will learn the basics of polling and be able to analyze and explain polling and survey data • Students will learn the basics of research design and be able to critically analyze the advantages and disadvantages of different types of design.
Sampling After we write the survey, we have to select people!
Why? Non-Probability Samples
Quota Samples • A Type of Judgment Sample • Break the nation into groups • Pick a certain number/quota from each group • Stop when you have filled up your quota
The Death of Quota Sampling: 1948 • We used to use these for national polls • George Gallup thrived on these. • In 1948 he predicts that Thomas Dewey of New York would defeat Harry Truman
Why Gallup was Wrong • It was a close election • The electorate diversified (missed out on groups) • They filled up quotas with easy targets • They stopped polling
Snowball Sample • one becomes two, becomes four, becomes 8 • Difficult to Reach Populations • Background Checks
Looking through A Parent’s eyes The Most Beautiful Kids Ever Internal Polling
The Laws of Sampling • if cost is not a major consideration it is better to collect data for ones target population than for a sample thereof • if cost dictates that a sample be drawn, a probability sample is usually preferable to a nonprobability sample. • The Law of Large Numbers • The accuracy of estimates is expressed in terms of the margin or error and the confidence level. • all probability samples yield estimates of the target population.
Rules on Sampling • if cost dictates that a sample be drawn, a probability sample is usually preferable to a nonprobability sample. • The Law of Large Numbers
Collecting a sample • Population • Sampling Frame • The Sample itself
Probability Samples • Ensure that every unit in the population has an equal chance of being selected • In a simple random sample all elements in the population can be selected (SRS) • This involves having a full list of everyone! • We cannot do a SRS of the United States
The best that we can hope for is that every unit in the sampling frame has an equal chance of being selected
How to do it- Simple Way Random Number Table The Lottery Method
The Law of Large Numbers • Smaller samples cause greater error. • The larger the sample size, the greater the probability that our sample will represent the population.
All probability samples yield estimates of the target population
Two Things that Deal With the Stars Astronomy Astrology
Polling is Science (Astronomy) • Polls are right more than they are wrong • We especially love them when it favors our candidates.
Polling is Random (Astrology) • It is not an exact science, there is error in every poll. • Polls Don’t Vote, People Vote • We like it less when it doesn’t favor our candidate
Different Questions Perhaps? • If the election were held today, would you vote for Barack Obama or Mitt Romney? • If the election were held today, would you vote for Mitt Romney or Barack Obama? • If the election were held today, would you vote for Democrat Barack Obama or Republican Mitt Romney? • If the election were held today, would you vote for Republican Mitt Romney or Democrat Barack Obama? • If the election were held today, for whom would you vote?
Polling is 95% Science and 5% Astrology Sampling error
The accuracy of estimates is expressed in terms of the margin or error and the confidence level
The Confidence Level • The Confidence Level- can we trust these results? • Surveys use a 95% confidence interval that the results will fall within the margin of error • There is a 5% (1 out of 20) chance that the results will fall outside this range and produce wacky findings. • This error often appears when you keep asking the same questions again and again
The Margin of Error • Margin of Error • A floating range above and below the estimate. • Large Samples= Less Error
What else determines sampling error • Non-response rate • Variability • Bias
How Can a Survey of 1000 People Represent Millions of Voters? • Responses Cancel each other out • No New opinions are added