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https://doi.org/10.12758/mda.2014.001

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The accuracy of pre-election polling of German general elections

[journal article]

Schnell, Rainer
Noack, Marcel

Abstract

"Pre-election polls are the most prominent type of surveys. As with any other survey, estimates are only of interest if they do not deviate significantly from the true state of nature. Even though pre-election polls in Germany as well as in other countries repeatedly show noticeably inaccurate resu... view more

"Pre-election polls are the most prominent type of surveys. As with any other survey, estimates are only of interest if they do not deviate significantly from the true state of nature. Even though pre-election polls in Germany as well as in other countries repeatedly show noticeably inaccurate results, their failure appears to be quickly forgotten. No comparison considering all available German data on actual election results and the confidence intervals based on pre-election polls has been published. In the study reported here only 69% of confidence intervals covered the election result, whereas statistically 95% would have to be expected. German pre-election polls even just a month ahead are therefore much less accurate than most introductory statistical textbooks would suggest." (author's abstract)... view less

Keywords
election research; prognosis; voting behavior; estimation; public opinion; survey research; sampling error; election to the Bundestag; Federal Republic of Germany

Classification
Political Process, Elections, Political Sociology, Political Culture
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods

Free Keywords
Pre-Election-Polls; empirical coverage; confidence intervals for binomial data; design effects; Sonntagsfrage

Document language
English

Publication Year
2014

Page/Pages
p. 5-24

Journal
Methods, data, analyses : a journal for quantitative methods and survey methodology (mda), 8 (2014) 1

ISSN
2190-4936

Status
Published Version; peer reviewed

Licence
Creative Commons - Attribution


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© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.