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## Random and Non-Random samples

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**Random and Non-Random samples**12/3/2013**Readings**• Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)**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**Final Exam**• SEC 1 • December 11th (Wednesday) • 1:30 pm - 3:30 pm • SEC 2 • December 10th (Tuesday) • 1:30 pm - 3:30 pm**Final Paper**• Due 12/6/2013 by 11:59 AM- Doyle 226B • Turnitin via Blackboard Copy by 11:59PM on 12/6**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**Paste as an Image**• Paste outputs into the paper as images**Running X-tabs**• Don’t forget column %’s, measures of association, chi-square**Office Hours For the Week**• When • Wednesday 7-9, 10-3:30 • Thursday 7-12 • 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!**Collecting a sample**• Population • Sampling Frame • The Sample itself**The Practicality of Sampling**• Time • Money • Size**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.**Why?**Non-Probability Samples**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**Why Non-Probability**• Very Fast • Very cheap • Difficult Populations to reach • Exploration**Business Uses this Extensively**• Get the Product out • Focus Groups • Alternate endings • Test audiences • If it works, you expand**Self Selected Samples**• People Choose to Be in the Sample • Certain people have much more incentive to participate**Straight-up Internet Surveys**• These are self-selected • Big numbers mean nothing**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)**Why The Literary Digest was Wrong**• The wrong sampling frame • Response bias • The Literary Digest goes out of business**Convenience Samples**• Super-Fast • Pick easy targets**Purposive/Judgment Samples**• Find People who Match your criteria • The Price is Right • Easy, but Not random… not representative**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**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