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Random Samples

Random Samples. 12/5/2013. Readings. Chapter 6 Foundations of Statistical Inference (Pollock) ( pp 122-135 ). Final Exam. SEC 1 December 11 th (Wednesday) 1:30 pm - 3:30 pm SEC 2 December 10 th (Tuesday) 1:30 pm - 3:30 pm. Final Paper. Due 12/6/2013 by 11:59 AM- Doyle 226B

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Random Samples

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  1. Random Samples 12/5/2013

  2. Readings • Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

  3. Final Exam • SEC 1 • December 11th (Wednesday) • 1:30 pm - 3:30 pm • SEC 2 • December 10th (Tuesday) • 1:30 pm - 3:30 pm

  4. Final Paper • Due 12/6/2013 by 11:59 AM- Doyle 226B • Turnitin via Blackboard Copy by 11:59PM on 12/6

  5. Reminders for the Paper • Dataset information is in Chapter 1 and in the appendix (p. 2-4). GSS and NES also has information on line • World.sav- http://www.hks.harvard.edu/fs/pnorris/Data/Data.htm • If running x-tabs don’t forget column %’s

  6. Opportunities to discuss course content

  7. Office Hours For the Week • When • Friday 7-12 • No Office hours during final exam week • And by appointment

  8. 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.

  9. Sampling After we write the survey, we have to select people!

  10. 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

  11. Collecting a sample • Population • Sampling Frame • The Sample itself

  12. The best that we can hope for is that every unit in the sampling frame has an equal chance of being selected

  13. 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.

  14. All probability samples yield estimates of the target population

  15. Two Things that Deal With the Stars Astronomy Astrology

  16. Polling is Science (Astronomy) • Polls are right more than they are wrong • We especially love them when it favors our candidates.

  17. 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

  18. Same Election, Different Results

  19. 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?

  20. More likely a different sample

  21. Polling is 95% Science and 5% Astrology Sampling error

  22. The accuracy of estimates is expressed in terms of the margin or error and the confidence level

  23. 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

  24. The Margin of Error • Margin of Error • A floating range above and below the estimate. • Large Samples= Less Error

  25. Still too early PPP POLL Texas Tribune Poll

  26. On these Polls PPP Texas Tribune Abbott could be leading by as much as 42.83 to 31.17 The Race could be as close as 37.17 to 36.83 for Abbott Races that fall within the margin of error we say “too close to call”. • Abbott could be leading by as much as 54.4 to 30.6 • The Race could be as close as 45.6-39.4

  27. What else determines sampling error • Non-response rate • Variability • Bias

  28. How Can a Survey of 1000 People Represent Millions of Voters? • Responses Cancel each other out • No New opinions are added

  29. Its Logarithmic

  30. Data Collection Method I Personal Interviews

  31. Cluster Sampling (How we conduct it) • People Move, Houses Don’t • Random Samples of known units • Each unit in the cluster has a chance

  32. BLS

  33. Personal Interviews • Advantages • Disadvantages

  34. Method II Mail Surveys

  35. Collecting a Sample • Every address is in our frame • Often Used to target specific Groups • Less popular for “hot topics”

  36. About Mail • Advantages • Disadvantages

  37. How Most Surveys are Done Today Telephone Surveys

  38. Telephone Surveys • Every Phone Number has an equal Chance of Being Selected • It is important that you select the right people

  39. Advantages of Phone • Fast • CATI • Closed Ended Questions

  40. Why it is not a true random sample • Some people do not have phones • Some people simply will not answer (75% refusal rate)

  41. Surveys miss out on • Poll Sampling excludes many—minorities, young people, and new Americans • Angry White Men

  42. Who we often get

  43. Problems of Cell Phones • Some polls Exclude them • You have to pay people to participate • Some polls contact you and ask you to call back

  44. Exit Polls • Use a random selection of polling places • Quick Recall and Fast Data • Problems (early voting)

  45. This makes it less random We have to survey a lot more people than we used to

  46. Not All Sampling Frames are Created Equal

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