andrew_gelman_stats andrew_gelman_stats-2012 andrew_gelman_stats-2012-1313 knowledge-graph by maker-knowledge-mining
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Introduction: 1. Suppose that, in a survey of 1000 people in a state, 400 say they voted in a recent primary election. Actually, though, the voter turnout was only 30%. Give an estimate of the probability that a nonvoter will falsely state that he or she voted. (Assume that all voters honestly report that they voted.) P.S. The commenters are picking up some of the unintended “Hare and pineapple” ambiguity in my question!
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1 Suppose that, in a survey of 1000 people in a state, 400 say they voted in a recent primary election. [sent-2, score-0.7]
2 Give an estimate of the probability that a nonvoter will falsely state that he or she voted. [sent-4, score-1.009]
3 (Assume that all voters honestly report that they voted. [sent-5, score-0.538]
4 The commenters are picking up some of the unintended “Hare and pineapple” ambiguity in my question! [sent-8, score-0.87]
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same-blog 1 1.0 1313 andrew gelman stats-2012-05-11-Question 1 of my final exam for Design and Analysis of Sample Surveys
Introduction: 1. Suppose that, in a survey of 1000 people in a state, 400 say they voted in a recent primary election. Actually, though, the voter turnout was only 30%. Give an estimate of the probability that a nonvoter will falsely state that he or she voted. (Assume that all voters honestly report that they voted.) P.S. The commenters are picking up some of the unintended “Hare and pineapple” ambiguity in my question!
2 0.37196755 1315 andrew gelman stats-2012-05-12-Question 2 of my final exam for Design and Analysis of Sample Surveys
Introduction: 2. Which of the following are useful goals in a pilot study? (Indicate all that apply.) (a) You can search for statistical significance, then from that decide what to look for in a confirmatory analysis of your full dataset. (b) You can see if you find statistical significance in a pre-chosen comparison of interest. (c) You can examine the direction (positive or negative, even if not statistically significant) of comparisons of interest. (d) With a small sample size, you cannot hope to learn anything conclusive, but you can get a crude estimate of effect size and standard deviation which will be useful in a power analysis to help you decide how large your full study needs to be. (e) You can talk with survey respondents and get a sense of how they perceived your questions. (f) You get a chance to learn about practical difficulties with sampling, nonresponse, and question wording. (g) You can check if your sample is approximately representative of your population. Soluti
3 0.35510302 1307 andrew gelman stats-2012-05-07-The hare, the pineapple, and Ed Wegman
Introduction: Commenters here are occasionally bothered that I spend so much time attacking frauds and plagiarists. See, for example, here and here . Why go on and on about these losers, given that there are more important problems in the world such as war, pestilence, hunger, and graphs where the y-axis doesn’t go all the way down to zero? Part of the story is that I do research for a living so I resent people who devalue research through misattribution or fraud, in the same way that rich people don’t like counterfeiters. What really bugs me, though, is when cheaters get caught and still don’t admit it. People like Hauser, Wegman, Fischer, and Weick get under my skin because they have the chutzpah to just deny deny deny. The grainy time-stamped videotape with their hand in the cookie jar is right there, and they’ll still talk around the problem. Makes me want to scream. This happens all the time . All. Over. The. Place. Everybody makes mistakes, and just about everybody does thing
4 0.1283983 898 andrew gelman stats-2011-09-10-Fourteen magic words: an update
Introduction: In the discussion of the fourteen magic words that can increase voter turnout by over 10 percentage points , questions were raised about the methods used to estimate the experimental effects. I sent these on to Chris Bryan, the author of the study, and he gave the following response: We’re happy to address the questions that have come up. It’s always noteworthy when a precise psychological manipulation like this one generates a large effect on a meaningful outcome. Such findings illustrate the power of the underlying psychological process. I’ve provided the contingency tables for the two turnout experiments below. As indicated in the paper, the data are analyzed using logistic regressions. The change in chi-squared statistic represents the significance of the noun vs. verb condition variable in predicting turnout; that is, the change in the model’s significance when the condition variable is added. This is a standard way to analyze dichotomous outcomes. Four outliers were excl
5 0.12745441 678 andrew gelman stats-2011-04-25-Democrats do better among the most and least educated groups
Introduction: These are based on raw Pew data, reweighted to adjust for voter turnout by state, income, and ethnicity. No modeling of vote on age, education, and ethnicity. I think our future estimates based on the 9-way model will be better, but these are basically OK, I think. All but six of the dots in the graph are based on sample sizes greater than 30. I published these last year but they’re still relevant, I think. There’s lots of confusion when it comes to education and voting.
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Introduction: 1. Suppose that, in a survey of 1000 people in a state, 400 say they voted in a recent primary election. Actually, though, the voter turnout was only 30%. Give an estimate of the probability that a nonvoter will falsely state that he or she voted. (Assume that all voters honestly report that they voted.) P.S. The commenters are picking up some of the unintended “Hare and pineapple” ambiguity in my question!
2 0.76230121 1356 andrew gelman stats-2012-05-31-Question 21 of my final exam for Design and Analysis of Sample Surveys
Introduction: 21. A country is divided into three regions with populations of 2 million, 2 million, and 0.5 million, respectively. A survey is done asking about foreign policy opinions.. Somebody proposes taking a sample of 50 people from each reason. Give a reason why this non-proportional sample would not usually be done, and also a reason why it might actually be a good idea. Solution to question 20 From yesterday : 20. Explain in two sentences why we expect survey respondents to be honest about vote preferences but possibly dishonest about reporting unhealty behaviors. Solution: Respondents tend to be sincere about vote preferences because this affects the outcome of the poll, and people are motivated to have their candidate poll well. This motivation is typically not present in reporting behaviors; you have no particular reason for wanting to affect the average survey response.
3 0.70025766 1371 andrew gelman stats-2012-06-07-Question 28 of my final exam for Design and Analysis of Sample Surveys
Introduction: This is it, the last question on the exam! 28. A telephone survey was conducted several years ago, asking people how often they were polled in the past year. I can’t recall the responses, but suppose that 40% of the respondents said they participated in zero surveys in the previous year, 30% said they participated in one survey, 15% said two surveys, 10% said three, and 5% said four. From this it is easy to estimate an average, but there is a worry that this survey will itself overrepresent survey participants and thus overestimate the rate at which the average person is surveyed. Come up with a procedure to use these data to get an improved estimate of the average number of surveys that a randomly-sampled American is polled in a year. Solution to question 27 From yesterday : 27. Which of the following problems were identified with the Burnham et al. survey of Iraq mortality? (Indicate all that apply.) (a) The survey used cluster sampling, which is inappropriate for estim
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Introduction: 2. Which of the following are useful goals in a pilot study? (Indicate all that apply.) (a) You can search for statistical significance, then from that decide what to look for in a confirmatory analysis of your full dataset. (b) You can see if you find statistical significance in a pre-chosen comparison of interest. (c) You can examine the direction (positive or negative, even if not statistically significant) of comparisons of interest. (d) With a small sample size, you cannot hope to learn anything conclusive, but you can get a crude estimate of effect size and standard deviation which will be useful in a power analysis to help you decide how large your full study needs to be. (e) You can talk with survey respondents and get a sense of how they perceived your questions. (f) You get a chance to learn about practical difficulties with sampling, nonresponse, and question wording. (g) You can check if your sample is approximately representative of your population. Soluti
Introduction: A reporter emailed me the other day with a question about a case I’d never heard of before, a company called Herbalife that is being accused of being a pyramid scheme. The reporter pointed me to this document which describes a survey conducted by “a third party firm called Lieberman Research”: Two independent studies took place using real time (aka “river”) sampling, in which respondents were intercepted across a wide array of websites Sample size of 2,000 adults 18+ matched to U.S. census on age, gender, income, region and ethnicity “River sampling” in this case appears to mean, according to the reporter, that “people were invited into it through online ads.” The survey found that 5% of U.S. households had purchased Herbalife products during the past three months (with a “0.8% margin of error,” ha ha ha). They they did a multiplication and a division to estimate that only 8% of households who bought these products were Herbalife distributors: 480,000 active distributor
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Introduction: 1. Suppose that, in a survey of 1000 people in a state, 400 say they voted in a recent primary election. Actually, though, the voter turnout was only 30%. Give an estimate of the probability that a nonvoter will falsely state that he or she voted. (Assume that all voters honestly report that they voted.) P.S. The commenters are picking up some of the unintended “Hare and pineapple” ambiguity in my question!
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Introduction: Yesterday Aleks posted a proposal for a model makers’ Hippocratic Oath. I’d like to add two more items: 1. From Mark Palko : “Our model only describes the data we used to build it; if you go outside of that range, you do so at your own risk.” 2. In case you like to think of your methods as nonparametric or non-model-based: “Our method, just like any model, relies on assumptions which we have the duty to state and to check.” (Observant readers will see that I use “we” rather than “I” in these two items. Modeling is an inherently collaborative endeavor.
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