Report

Austin Cole February 16, 2010 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 Sampling Population- entire group of individuals about which we want information Sample- part of population from which information is collected Unemployment Monthly unemployment rate based on survey of 60,000 households Define population Define unemployed Final percentage "Labor Force" Unemployed Not looking for work Employed 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 Simple Random Sampling Every individual in population has equal chance to be sampled Table of random digits Cautions about Sample Surveys Undercoverage-group of the population is left out when choosing sample Nonresponse-individual chosen doesn’t participate Wording of questions Experiments Observational Study Experiment-imposes some treatment on individuals to observe their responses Confounding variables-variable whose effects cannot be distinguished Control group Randomized Comparative Experiment Online vs. classroom courses 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 Thinking about Experiments Placebo effect Double-blind experiment Prospective studies 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 Simulation Assessing simulations Shape Center-mean of sampling distribution (g) Spread-standard deviation of sampling distribution g(1- g) n 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: 2 ĝ(1- ĝ) n 95% Confidence Interval 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=.42 ĝ(1- ĝ) n =.023 95% Confidence Interval: .376 to .466 Discussion In real world examples, what are some uses of knowing the spread/standard deviation? Other uses/applications for this information? Homework Problems: 9,38,44a (7th edition)