13 Collecting Statistical Data
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10 Questions Opinion Polls
Questions you might have on 10opinion polls 1. What is an opinion poll? An opinion poll is a survey carried out to measure views on a certain topic within a specific group of people. For example, the topic may relate to who Kenyans support in the presidential race, in which case, the group of people interviewed will be registered voters. 2. How are interviewees for an opinion poll selected? The group of people interviewed for an opinion poll is called a sample. As the name suggests, a sample is a group of people that represents the total population whose opinion is being surveyed. In a scientific opinion poll, everyone has an equal chance of being interviewed. 3. So how come I have never been interviewed for an opinion poll? You have the same chance of being polled as anyone else living in Kenya. However, chances of this are very small and are estimated at about 1 in 14,000. This is because there are approximately 14 million registered voters in Kenya and, for practical and cost reasons, usually only between 1,000 and 2,000 people are interviewed for each survey carried out. 4. How can such a small group be representative of the entire population? In order to ensure that the sample/survey group is representative of the population, the surveyors must ensure that the group reflects the characteristics of the whole. For instance, to get a general idea of who might win the Kenyan presidential election, only the views of registered voters in Kenya will be surveyed as these are the people who will be able to influence the election. -
Random Selection in Politics
Random selection in politics Lyn Carson and Brian Martin Published in 1999 by Praeger Publishers, Westport, CT Available for purchase from Praeger This is the text submitted to Praeger in February 1999. It differs from the published version in minor ways, including formatting, copy-editing changes, page numbering (100 pages instead of 161) and omission of the index. This version prepared August 2008 Contents 1. Introduction 1 2. Random selection in decision making 10 3. Direct democracy 26 4. Citizen participation without random selection 36 5. Citizen participation with random selection: the early days 43 6. Citizen participation with random selection: yesterday, today, and tomorrow 52 7. Sortition futures 65 8. Strategies 76 Appendix: Examples of citizen participation 84 Bibliography 93 Acknowledgments Brownlea, John Burnheim, Ned Crosby, Many people we’ve talked to find the Jim Dator, Mary Lane, Marcus Schmidt, idea of random selection in politics and Stuart White. Their input was unnatural and unwelcome. This didn’t valuable even when we decided on an deter us! Fortunately, there were a few alternative approach. Helpful comments enthusiasts who got and kept us going. were also received from Ted Becker, Alan Davies, Fred Emery, and Merrelyn Stephen Healy, Lars Klüver, and Ken Emery provided the original inspiration Russell. Others who provided many years ago as well as ongoing information are acknowledged in the conversations. text. The process of obtaining comments Ted Becker encouraged us to write has been stimulating because not all this book. On drafts, we received readers go with us all the way on extensive comments from Arthur randomness. -
The Effect of Sampling Error on the Time Series Behavior of Consumption Data*
Journal of Econometrics 55 (1993) 235-265. North-Holland The effect of sampling error on the time series behavior of consumption data* William R. Bell U.S.Bureau of the Census, Washington, DC 20233, USA David W. Wilcox Board of Governors of the Federal Reserve System, Washington, DC 20551, USA Much empirical economic research today involves estimation of tightly specified time series models that derive from theoretical optimization problems. Resulting conclusions about underly- ing theoretical parameters may be sensitive to imperfections in the data. We illustrate this fact by considering sampling error in data from the Census Bureau’s Retail Trade Survey. We find that parameter estimates in seasonal time series models for retail sales are sensitive to whether a sampling error component is included in the model. We conclude that sampling error should be taken seriously in attempts to derive economic implications by modeling time series data from repeated surveys. 1. Introduction The rational expectations revolution has transformed the methodology of macroeconometric research. In the new style, the researcher typically begins by specifying a dynamic optimization problem faced by agents in the model economy. Then the researcher derives the solution to the optimization problem, expressed as a stochastic model for some observable economic variable(s). A trademark of research in this tradition is that each of the parameters in the model for the observable variables is endowed with a specific economic interpretation. The last step in the research program is the application of the model to actual economic data to see whether the model *This paper reports the general results of research undertaken by Census Bureau and Federal Reserve Board staff. -
Preface Chapter 1
Notes Preface 1. Alfred Pearce Dennis, “Humanizing the Department of Commerce,” Saturday Evening Post, June 6, 1925, 8. 2. Herbert Hoover, Memoirs: The Cabinet and the Presidency, 1920–1930 (New York: Macmillan, 1952), 184. 3. Herbert Hoover, “The Larger Purposes of the Department of Commerce,” in “Republi- can National Committee, Brief Review of Activities and Policies of the Federal Executive Departments,” Bulletin No. 6, 1928, Herbert Hoover Papers, Campaign and Transition Period, Box 6, “Subject: Republican National Committee,” Hoover Presidential Library, West Branch, Iowa. 4. Herbert Hoover, “Responsibility of America for World Peace,” address before national con- vention of National League of Women Voters, Des Moines, Iowa, April 11, 1923, Bible no. 303, Hoover Presidential Library. 5. Bruce Bliven, “Hoover—And the Rest,” Independent, May 29, 1920, 275. Chapter 1 1. John W. Hallowell to Arthur (Hallowell?), November 21, 1918, Hoover Papers, Pre-Com- merce Period, Hoover Presidential Library, West Branch, Iowa, Box 6, “Hallowell, John W., 1917–1920”; Julius Barnes to Gertrude Barnes, November 27 and December 5, 1918, ibid., Box 2, “Barnes, Julius H., Nov. 27, 1918–Jan. 17, 1919”; Lewis Strauss, “Further Notes for Mr. Irwin,” ca. February 1928, Subject File, Lewis L. Strauss Papers, Hoover Presidential Library, West Branch, Iowa, Box 10, “Campaign of 1928: Campaign Literature, Speeches, etc., Press Releases, Speeches, etc., 1928 Feb.–Nov.”; Strauss, handwritten notes, December 1, 1918, ibid., Box 76, “Strauss, Lewis L., Diaries, 1917–19.” 2. The men who sailed with Hoover to Europe on the Olympic on November 18, 1918, were Julius Barnes, Frederick Chatfi eld, John Hallowell, Lewis Strauss, Robert Taft, and Alonzo Taylor. -
American Community Survey Accuracy of the Data (2018)
American Community Survey Accuracy of the Data (2018) INTRODUCTION This document describes the accuracy of the 2018 American Community Survey (ACS) 1-year estimates. The data contained in these data products are based on the sample interviewed from January 1, 2018 through December 31, 2018. The ACS sample is selected from all counties and county-equivalents in the United States. In 2006, the ACS began collecting data from sampled persons in group quarters (GQs) – for example, military barracks, college dormitories, nursing homes, and correctional facilities. Persons in sample in (GQs) and persons in sample in housing units (HUs) are included in all 2018 ACS estimates that are based on the total population. All ACS population estimates from years prior to 2006 include only persons in housing units. The ACS, like any other sample survey, is subject to error. The purpose of this document is to provide data users with a basic understanding of the ACS sample design, estimation methodology, and the accuracy of the ACS data. The ACS is sponsored by the U.S. Census Bureau, and is part of the Decennial Census Program. For additional information on the design and methodology of the ACS, including data collection and processing, visit: https://www.census.gov/programs-surveys/acs/methodology.html. To access other accuracy of the data documents, including the 2018 PRCS Accuracy of the Data document and the 2014-2018 ACS Accuracy of the Data document1, visit: https://www.census.gov/programs-surveys/acs/technical-documentation/code-lists.html. 1 The 2014-2018 Accuracy of the Data document will be available after the release of the 5-year products in December 2019. -
George Gallup: Highlights of His Life and Work
George Gallup: Highlights of His Life and Work PRE-BIOGRAPHY AND PRE-HISTORY Understanding the character of creative people and the significance of their achievements requires, in the first place, a study of their pre-biography, together with the pre-history of that branch of science, art or culture where their endeavors have taken place. In other words, the person’s biography is a product of both the genealogy and the environment in which his or her professional activity has taken place. The life and work of George Gallup in this sense are exemplary. In the first place, he belonged to a large family, whose members had vigorously participated in the development of the United States, and whose accomplishments and merits are recorded in the annals of the country. Secondly, even though the modern stage of public opinion research began with the pioneering work of George Gallup in 1935 and 1936, the study of electoral attitudes in the US had a long history prior to that. Accordingly, after examining the pre-biography of George Gallup, we will also review the pre-history of public opinion research. Tenth-Generation American For generations, the large Kollop family resided in Lotharingia (Lorraine). During the Middle Ages some of its descendants moved over to England, retaining the Gollop name. It is believed to have been forged from the German words Gott and Lobe, meaning respectively “God” and “praise”. Over time various spellings of the family name emerged: Gallop, Galloup, Galloupe, Gallupe, and Gollop, with the version prevalent in America becoming Gal- lup. A historical record has been preserved in England concerning John Gollop (born about 1440), who came ‘out of the North in the fifth year of the reign of Edward IV’ (1465). -
MRS Guidance on How to Read Opinion Polls
What are opinion polls? MRS guidance on how to read opinion polls June 2016 1 June 2016 www.mrs.org.uk MRS Guidance Note: How to read opinion polls MRS has produced this Guidance Note to help individuals evaluate, understand and interpret Opinion Polls. This guidance is primarily for non-researchers who commission and/or use opinion polls. Researchers can use this guidance to support their understanding of the reporting rules contained within the MRS Code of Conduct. Opinion Polls – The Essential Points What is an Opinion Poll? An opinion poll is a survey of public opinion obtained by questioning a representative sample of individuals selected from a clearly defined target audience or population. For example, it may be a survey of c. 1,000 UK adults aged 16 years and over. When conducted appropriately, opinion polls can add value to the national debate on topics of interest, including voting intentions. Typically, individuals or organisations commission a research organisation to undertake an opinion poll. The results to an opinion poll are either carried out for private use or for publication. What is sampling? Opinion polls are carried out among a sub-set of a given target audience or population and this sub-set is called a sample. Whilst the number included in a sample may differ, opinion poll samples are typically between c. 1,000 and 2,000 participants. When a sample is selected from a given target audience or population, the possibility of a sampling error is introduced. This is because the demographic profile of the sub-sample selected may not be identical to the profile of the target audience / population. -
Has Polling Enhanced Representation? Unearthing Evidence from the Literary Digest Issue Polls
Studies in American Political Development, 21 (Spring 2007), 16–29. Has Polling Enhanced Representation? Unearthing Evidence from the Literary Digest Issue Polls David Karol, University of California, Berkeley How has representation changed over time in the Institutional reforms are not, however, the only United States? Has responsiveness to public opinion factors that can affect representation; technological waxed or waned among elected officials? What are change can also play a significant role. In fact, some the causes of such trends as we observe? Scholars scholars contend that the rise of scientific surveys have pursued these crucial questions in different since the 1930s has yielded more responsive govern- ways. Some explore earlier eras in search of the “elec- ment. According to this school of thought, polls toral connection”, i.e. the extent to which voters held provide recent cohorts of elected officials more accu- office-holders accountable for their actions and the rate assessments of public opinion than their prede- degree to which electoral concerns motivated poli- cessors enjoyed, which allows them to reflect their ticians’ behavior.1 Others explore the effects of insti- constituents’ views to a greater extent than the tutional changes such as the move to direct election politicians of yesteryear. Yet others doubt whether of senators or the “reapportionment revolution.”2 politicians were truly ignorant of public sentiment before the rise of the poll; nor is there much certainty regarding the level of current politicians’ understand- I thank Larry Bartels, Terri Bimes, Ben Bishin, Ben Fordham, ing of constituent opinion. Some also question John Geer, Brian Glenn, Susan Herbst, Mark Kayser, Brian Lawson, whether ignorance is at the root of elected officials’ Taeku Lee, Eileen McDonagh and Eric Plutzer for comments along frequent divergence from their constituents’ wishes. -
Observational Studies and Bias in Epidemiology
The Young Epidemiology Scholars Program (YES) is supported by The Robert Wood Johnson Foundation and administered by the College Board. Observational Studies and Bias in Epidemiology Manuel Bayona Department of Epidemiology School of Public Health University of North Texas Fort Worth, Texas and Chris Olsen Mathematics Department George Washington High School Cedar Rapids, Iowa Observational Studies and Bias in Epidemiology Contents Lesson Plan . 3 The Logic of Inference in Science . 8 The Logic of Observational Studies and the Problem of Bias . 15 Characteristics of the Relative Risk When Random Sampling . and Not . 19 Types of Bias . 20 Selection Bias . 21 Information Bias . 23 Conclusion . 24 Take-Home, Open-Book Quiz (Student Version) . 25 Take-Home, Open-Book Quiz (Teacher’s Answer Key) . 27 In-Class Exercise (Student Version) . 30 In-Class Exercise (Teacher’s Answer Key) . 32 Bias in Epidemiologic Research (Examination) (Student Version) . 33 Bias in Epidemiologic Research (Examination with Answers) (Teacher’s Answer Key) . 35 Copyright © 2004 by College Entrance Examination Board. All rights reserved. College Board, SAT and the acorn logo are registered trademarks of the College Entrance Examination Board. Other products and services may be trademarks of their respective owners. Visit College Board on the Web: www.collegeboard.com. Copyright © 2004. All rights reserved. 2 Observational Studies and Bias in Epidemiology Lesson Plan TITLE: Observational Studies and Bias in Epidemiology SUBJECT AREA: Biology, mathematics, statistics, environmental and health sciences GOAL: To identify and appreciate the effects of bias in epidemiologic research OBJECTIVES: 1. Introduce students to the principles and methods for interpreting the results of epidemio- logic research and bias 2. -
Third Party Election Spending and the Charter
ELECTIONSPENDING AND THE CHARTER 429 LIBERTE, EGALITE, ARGENT: THIRD PARTY ELECTION SPENDING AND THE CHARTER 0 ANDREW GEDDIS Both the federal government and the courts have le gouvernementfederal et /es cours de Justice ont brought about changes in election law. The author apportedes modificationsa la loi electorate.l 'auteur reviews these recent changes In the legal landscape revolt le.r recents changementsdans le cadre legal that surroundelection mies. Inparticular third party entourant/es reg/es electorates, tout particulierement electionspending. Thequestions of "whatrules exist" /es depenseselectorates de tiers. la question,a savoir and "who shall make them" are particularly « quelles sont les reg/es qui existent II et « qui les importantto the discussionas this area of law tries to me/Ira en place ,, est particulierement importante reconcile individual interestsin liberty and equality dans celle discussionetant donne que ce domainedu in a democracy.The trio of SupremeC our/ of Canada droit teme de reconcilierles interets individuelset la decisions, Libman v. Quebec (A.G.), Thomson notion de liberte et d'egalite d'une democralie.Les Newspapersv. Canada (A.G.) and Sauve v. Canada trois dkisions de la Cour supreme du Canada. (Chief Electoral Officer), reveal ambiguity In the notamment Libman c. le Quebec (A.G.). Thomson Court's rationalefor limiting Individual liberty at Newspapersc. le Canada (A.G.)et Sauve c. le Canada electiontime. Thisambiguity Is broachedIn the recent (Directeur general des elections), manlfestent Supreme Court of Canada case of Harper v. Canada I 'amblg1111erelativement au raisonnementde la Cour (A.G.)where the Courtaccepted that Parliamentmay de limiter la liberte individuellependant un scrutm. -
Capturing the Effects of Public Opinion Polls on Voter Support in the NY 25Th Congressional Election
Rochester Institute of Technology RIT Scholar Works Theses 12-23-2014 Capturing the Effects of Public Opinion Polls on Voter Support in the NY 25th Congressional Election Heather Knappen Follow this and additional works at: https://scholarworks.rit.edu/theses Recommended Citation Knappen, Heather, "Capturing the Effects of Public Opinion Polls on Voter Support in the NY 25th Congressional Election" (2014). Thesis. Rochester Institute of Technology. Accessed from This Thesis is brought to you for free and open access by RIT Scholar Works. It has been accepted for inclusion in Theses by an authorized administrator of RIT Scholar Works. For more information, please contact [email protected]. Capturing the Effects of Public Opinion Polls on Voter Support in the NY 25th Congressional Election By Heather Knappen A Thesis Submitted in Partial Fulfillment of the Graduation Requirements for the Degree of Master of Science Department of Science, Technology and Public Policy College of Liberal Arts Rochester Institute of Technology Rochester, New York December 23, 2014 II Capturing the Effects of Public Opinion Polls on Voter Support in the NY 25th Congressional Election by Heather Knappen Masters of Science Science, Technology and Public Policy Thesis Submitted in Partial Fulfillment of the Graduation Requirements for the College of Liberal Arts/Public Policy Program at ROCHESTER INSTITUTE OF TECHNOLOGY Rochester, New York June 2014 Submitted by: Heather Knappen Signature Date Accepted by: Ron Hira, Thesis Advisor Department of Public Policy, R.I.T Signature Date Franz Foltz, Committee Member Department of Public Policy, R.I.T Signature Date Eric Hittinger, Committee Member Department of Public Policy, R.I.T Signature Date III Table of Contents Abstract .......................................................................................................................................... -
8 Analyzing and Interpreting Polls
8 Analyzing and Interpreting Polls Thus far, we have considered how public opinion surveys are conducted, how they are reported in the media, and how they influence elections and campaigns. This chapter focuses on the end products of public opinion surveys: the analysis and interpretation of poll data. Interpreting a poll is more an art than a science, even though statistical analysis of poll data is central to the enterprise. An investigator examining poll results has tremendous leeway in deciding which items to analyze, which sample subsets or breakdowns to present, and how to interpret the statistical results. Take, as an example, a poll with three items that mea- sure attitudes toward stem cell research. The investigator may construct an index from these three items, as discussed in Chapter 3. Or the inves- tigator may emphasize the results from one question, perhaps because of space and time constraints and the desire to keep matters simple or because those particular results best support the analyst’s own policy pref- erences. Another possibility is to examine the results from the entire sam- ple and ignore subgroups whose responses deviate from the overall pattern. Again, time and space limitations or the investigator’s own pref- erences may influence the choices. Finally, two investigators may interpret identical poll results in sharply different ways depending on the perspec- tives and values they bring to their data analysis; the glass may be half full or half empty. The analysis and interpretation of poll data entail a high degree of Dosubjectivity not and judgment.copy, Subjectivity, post, in this or context, distribute does not mean deliberate bias or distortion but simply professional judgments about the importance and relevance of information.