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Chapter 9 Section 1 MA1020 Quantitative Literacy Sidney Butler Michigan Technological University October 18, 2006 S Butler (Michigan Tech) Chapter 9 Section 1 October 18, 2006 1 / 9 Populations and Samples Population Elements Variable


  1. Chapter 9 Section 1 MA1020 Quantitative Literacy Sidney Butler Michigan Technological University October 18, 2006 S Butler (Michigan Tech) Chapter 9 Section 1 October 18, 2006 1 / 9

  2. Populations and Samples Population Elements Variable Census Sample S Butler (Michigan Tech) Chapter 9 Section 1 October 18, 2006 2 / 9

  3. Exercise #2 Identify the population being studied, the sample that is actually observed, and the variable. Divers recover a chest of 1000 gold coins from a sunken Spanish galleon found off the coast of Panama. The archaeologist working on the salvage project take 20 coins from the top of the chest and test them to see if they are pure gold. S Butler (Michigan Tech) Chapter 9 Section 1 October 18, 2006 3 / 9

  4. Data Quantitative Qualitative Ordinal Nominal S Butler (Michigan Tech) Chapter 9 Section 1 October 18, 2006 4 / 9

  5. Bias Representative sample Statistical inference Bias S Butler (Michigan Tech) Chapter 9 Section 1 October 18, 2006 5 / 9

  6. Common Sources of Bias in Surveys Faulty Sampling Faulty Questions Faulty Interviewing Lack of Understanding or Knowledge False Answers S Butler (Michigan Tech) Chapter 9 Section 1 October 18, 2006 6 / 9

  7. Exercise #14 Identify and discuss any sources of bias in the sampling method. A magazine devoted to exercise, vitamins, and healthy living is interested in the habits of older adults related to exercise and nutritional supplements. The current issue includes an article on the subject and a questionnaire for readers to fill out and mail in. S Butler (Michigan Tech) Chapter 9 Section 1 October 18, 2006 7 / 9

  8. Simple Random Samples Simple random sample Random-number generator S Butler (Michigan Tech) Chapter 9 Section 1 October 18, 2006 8 / 9

  9. Exercise #28 Professional baseball has 16 National League player representatives, one for each of the National League teams. The 2004 player representatives are listed in the following table. These players serve as representatives in labor negotiations. Suppose union leaders randomly select a special committee of 6 players from the 16 player representatives. National League Player Team Craig Counsell Arizona Diamondbacks Mike Remlinger Atlanta Braves Joe Girardi Chicago Cubs Aaron Boone Cincinnati Reds Todd Zeile Colorado Rockies Charles Johnson Florida Marlins Gregg Zaun Houston Astros Paul Lo Duca Los Angeles Dogers Ray King Milwaukee Brewers Michael Barrett Montreal Expos Al Leiter New York Mets S Butler (Michigan Tech) Chapter 9 Section 1 October 18, 2006 9 / 9 Doug Glanville Philadelphia Phillies

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