Random and Non-Random samples

# Random and Non-Random samples

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## Random and Non-Random samples

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1. Random and Non-Random samples 12/3/2013

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

3. Homework Due Today • Chapter 8 • Question 1: A, B,C,D • Question 2: A, B, C, D, E • Question 3: A, B, C • Question 4: A, B, C, D • Question 5: A, B, C, D, E, G

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

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

6. 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

7. Paste as an Image • Paste outputs into the paper as images

8. Running X-tabs • Don’t forget column %’s, measures of association, chi-square

9. Opportunities to discuss course content

10. Office Hours For the Week • When • Wednesday 7-9, 10-3:30 • Thursday 7-12 • And by appointment

11. 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.

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

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

14. The Practicality of Sampling • Time • Money • Size

15. The Laws of Sampling • The Law of Large Numbers • 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. • all probability samples yield estimates of the target population.  • The accuracy of estimates is expressed in terms of the margin of error and the confidence level.

16. Why? Non-Probability Samples

17. Probability vs. Non Probability • Probability- Every Unit Has a Chance of Being Selected • Also called a random sample • Non-Probability- some units have a greater chance of selection • Usually not generalizable

18. Why Non-Probability • Very Fast • Very cheap • Difficult Populations to reach • Exploration

19. Business Uses this Extensively • Get the Product out • Focus Groups • Alternate endings • Test audiences • If it works, you expand

20. Self Selected Samples • People Choose to Be in the Sample • Certain people have much more incentive to participate

21. Straight-up Internet Surveys • These are self-selected • Big numbers mean nothing

22. The Literary Digest in 1936 • Correct in 24,28,32 • 10 million ballots distributed • 2.2 Million Responses • Alf Landon Will defeat FDR (by a landslide)

23. Why The Literary Digest was Wrong • The wrong sampling frame • Response bias • The Literary Digest goes out of business

24. Convenience Samples • Super-Fast • Pick easy targets

25. Purposive/Judgment Samples • Find People who Match your criteria • The Price is Right • Easy, but Not random… not representative

26. 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

27. 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

28. 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

29. Snowball Sample • one becomes two, becomes four, becomes 8 • Difficult to Reach Populations • Background Checks

30. Looking through A Parent’s eyes The Most Beautiful Kids Ever Internal Polling

31. Probability Sampling

32. 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

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

34. 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

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

36. How to do it- Simple Way Random Number Table The Lottery Method

37. 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.

38. Two Things that Deal With the Stars Astronomy Astrology

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

40. 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

41. Same Election, Different Results

42. 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?

43. More likely a different sample

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

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

46. 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

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