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Random and Non-Random samples 12/3/2013

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Page 1: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Random and Non-Random samples

12/3/2013

Page 2: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Readings

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

Page 3: 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

Page 4: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Final Exam

• SEC 1– December 11th (Wednesday)– 1:30 pm - 3:30 pm

• SEC 2 – December 10th (Tuesday)– 1:30 pm - 3:30 pm

Page 5: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Final Paper

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

12/6

Page 6: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

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

Page 7: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Paste as an Image

• Paste outputs into the paper as images

Page 8: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Running X-tabs• Don’t forget column %’s, measures of

association, chi-square

Page 9: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

OPPORTUNITIES TO DISCUSS COURSE CONTENT

Page 10: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Office Hours For the Week

• When– Wednesday 7-9, 10-3:30– Thursday 7-12– And by appointment

Page 11: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Course Learning Objectives

1. Students will learn the basics of polling and be able to analyze and explain polling and survey data.

2. Students will learn the basics of research design and be able to critically analyze the advantages and disadvantages of different types of design.

Page 12: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Sampling

After we write the survey, we have to select people!

Page 13: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Collecting a sample

• Population

• Sampling Frame

• The Sample itself

Page 14: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

The Practicality of Sampling

• Time

• Money

• Size

Page 15: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

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.

Page 16: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

NON-PROBABILITY SAMPLESWhy?

Page 17: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

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

Page 18: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Why Non-Probability

• Very Fast

• Very cheap

• Difficult Populations to reach

• Exploration

Page 19: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Business Uses this Extensively

• Get the Product out– Focus Groups – Alternate endings – Test audiences

• If it works, you expand

Page 20: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Self Selected Samples

• People Choose to Be in the Sample

• Certain people have much more incentive to participate

Page 21: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Straight-up Internet Surveys

• These are self-selected

• Big numbers mean nothing

Page 22: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

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)

Page 23: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Why The Literary Digest was Wrong

• The wrong sampling frame

• Response bias

• The Literary Digest goes out of business

Page 24: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Convenience Samples

• Super-Fast

• Pick easy targets

Page 25: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Purposive/Judgment Samples

• Find People who Match your criteria

• The Price is Right

• Easy, but Not random… not representative

Page 26: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

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

Page 27: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

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

Page 28: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

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

Page 29: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Snowball Sample

• one becomes two, becomes four, becomes 8

• Difficult to Reach Populations

• Background Checks

Page 30: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Looking through A Parent’s eyes

The Most Beautiful Kids Ever Internal Polling

Page 31: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

PROBABILITY SAMPLING

Page 32: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

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

Page 33: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Collecting a sample

• Population

• Sampling Frame

• The Sample itself

Page 34: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

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

Page 35: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

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

Page 36: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

How to do it- Simple Way

Random Number Table The Lottery Method

Page 37: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

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.

Page 38: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

All probability samples yield estimates of the target population

Page 39: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Two Things that Deal With the Stars

Astronomy Astrology

Page 40: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Polling is Science (Astronomy)

• Polls are right more than they are wrong

• We especially love them when it favors our candidates.

Page 41: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)
Page 42: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

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

Page 43: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)
Page 44: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Same Election, Different Results

Poll Date Sample MoE Obama (D)

Romney (R) Spread

Rasmussen Tracking

10/4 - 10/6 1500 LV 3 47 49 Romney +2

Gallup Tracking

9/30 - 10/6 3050 RV 2 49 46 Obama +3

CNN/Opinion Research

9/28 - 9/30 783 LV 3.5 50 47 Obama +3

National Journal

9/27 - 9/30 789 LV 4.2 47 47 Tie

NBC News/WSJ

9/26 - 9/30 832 LV 3.4 49 46 Obama +3

NPR9/26 - 9/30 800 LV 4 51 44 Obama +7

ABC News/Wash Post

9/26 - 9/29 813 LV 4 49 47 Obama +2

Page 45: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

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?

Page 46: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

More likely a different sample

Page 47: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

SAMPLING ERRORPolling is 95% Science and 5% Astrology

Page 48: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

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

Page 49: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

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

Page 50: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

The Margin of Error

• Margin of Error

• A floating range above and below the estimate.

• Large Samples= Less Error

Page 51: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

What else determines sampling error

• Non-response rate

• Variability

• Bias

Page 52: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

How Can a Survey of 1000 People Represent Millions of Voters?

• Responses Cancel each other out

• No New opinions are added

Page 53: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Its Logarithmic

Page 54: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

PERSONAL INTERVIEWSData Collection Method I

Page 55: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Cluster Sampling (How we conduct it)

• People Move, Houses Don’t

• Random Samples of known units

• Each unit in the cluster has a chance

Page 56: Random and Non-Random samples 12/3/2013. Readings Chapter 6 Foundations of Statistical Inference (Pollock) (pp 122-135)

Personal Interviews

• Advantages

• Disadvantages