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Austin Cole February 16, 2010. Outline I. Sampling a. Bad Sampling Methods b. Random Sampling II. Experiments III. Applying Sample to a Population IV.

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Presentation on theme: "Austin Cole February 16, 2010. Outline I. Sampling a. Bad Sampling Methods b. Random Sampling II. Experiments III. Applying Sample to a Population IV."— Presentation transcript:

1 Austin Cole February 16, 2010

2 Outline I. Sampling a. Bad Sampling Methods b. Random Sampling II. Experiments III. Applying Sample to a Population IV. Simulations V. Confidence Intervals VI. Discussion

3 Sampling Population- entire group of individuals about which we want information Sample- part of population from which information is collected

4 Unemployment Monthly unemployment rate based on survey of 60,000 households Define population Define unemployed Final percentage

5 "Labor Force"

6 Bad Sampling Methods Convenience sample-sample of easiest to reach members of population Bias-systematically favoring a certain outcome Voluntary Response Sample-people choose to respond to a general appeal

7 Simple Random Sampling Every individual in population has equal chance to be sampled Table of random digits

8 Cautions about Sample Surveys Undercoverage-group of the population is left out when choosing sample Nonresponse-individual chosen doesn’t participate Wording of questions

9 Experiments Observational Study Experiment-imposes some treatment on individuals to observe their responses Confounding variables-variable whose effects cannot be distinguished Control group

10 Randomized Comparative Experiment Online vs. classroom courses

11 Random Sampling Exercise 1.Starting on line x, read 2-digit groups until you have chosen 6 restaurants. 2.Ignore groups not in the range and ignore any repeated labels. Starting at line 105: 07, 19, 14, 17, 13, 15

12 Thinking about Experiments Placebo effect Double-blind experiment Prospective studies

13 From Sample to Population Statistical inference-using fact of a sample to estimate about whole population Parameter-fixed number that describes population Statistic-number that describes a sample Sampling Distribution-distribution of values taken by the statistic in all possible samples of the same size from the same population

14 Simulation

15 Assessing simulations Shape Center-mean of sampling distribution (g) Spread-standard deviation of sampling distribution g(1- g) n

16 Confidence Intervals Percent of all samples will produce an interval containing the true population parameter 68-95-99.7 Rule Margin of error for 95% confidence interval: ĝ(1- ĝ) n 2

17 95% Confidence Interval

18 Exercise A Gallup poll asked a random sample of 1785 adults if they attended church or synagogue in the last 7 days. Of the respondents, 750 said yes. Find the 95% confidence interval. ĝ(1- ĝ) n ĝ=.42 =.023 95% Confidence Interval:.376 to.466

19 Discussion In real world examples, what are some uses of knowing the spread/standard deviation? Other uses/applications for this information? 9,38,44a (7 th edition) 9,38,44a (7 th edition) Homework Problems:


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