Colignatus, Thomas (2018): An overview of the elementary statistics of correlation, R-squared, cosine, sine, and regression through the origin, with application to votes and seats for Parliament.
Preview |
PDF
MPRA_paper_84722.pdf Download (360kB) | Preview |
Abstract
The correlation between two vectors is the cosine of the angle between the centered data. While the cosine is a measure of association, the literature has spent little attention to the use of the sine as a measure of distance. A key application of the sine is a new “sine-diagonal inequality / disproportionality” (SDID) measure for votes and their assigned seats for parties for Parliament. This application has nonnegative data and uses regression through the origin (RTO) with non-centered data. Textbooks are advised to discuss this case because the geometry will improve the understanding of both regression and the distinction between descriptive statistics and statistical decision theory. Regression may better be introduced and explained by looking at the angles relevant for a vector and its estimate rather than looking at the Euclidean distance and the sum of squared errors. The paper provides an overview of the issues involved. Also a new relation between the sine and the Euclidean distance is derived.
Item Type: | MPRA Paper |
---|---|
Institution: | Thomas Cool Consultancy & Econometrics |
Original Title: | An overview of the elementary statistics of correlation, R-squared, cosine, sine, and regression through the origin, with application to votes and seats for Parliament |
Language: | English |
Keywords: | General Economics, Social Choice, Social Welfare, Election, Parliament, Party System, Representation, Sine Diagonal Inequality / Disproportionality, SDID, Proportion, District, Voting, Seat, Euclid, Distance, Cosine, Sine, Gallagher, Loosemore-Hanby, Sainte-Laguë, Webster, Jefferson, Hamilton, Largest Remainder, Correlation, Diagonal regression, Regression through the origin, Apportionment, Disproportionality, Equity, Inequality |
Subjects: | A - General Economics and Teaching > A1 - General Economics > A10 - General D - Microeconomics > D6 - Welfare Economics > D63 - Equity, Justice, Inequality, and Other Normative Criteria and Measurement D - Microeconomics > D7 - Analysis of Collective Decision-Making > D71 - Social Choice ; Clubs ; Committees ; Associations D - Microeconomics > D7 - Analysis of Collective Decision-Making > D72 - Political Processes: Rent-Seeking, Lobbying, Elections, Legislatures, and Voting Behavior |
Item ID: | 84722 |
Depositing User: | Thomas Colignatus |
Date Deposited: | 21 Feb 2018 05:26 |
Last Modified: | 26 Sep 2019 13:39 |
References: | Colignatus is the name in science of Thomas Cool, econometrician and teacher of mathematics, Scheveningen, Holland, http://econpapers.repec.org/RAS/pco170.htm References in the text to Wikipedia refer to it as a portal and no source. Balinski, M. and H.P. Young (1976), "Criteria for proportional representation", IIASA Research Report December, RR-76-020, http://pure.iiasa.ac.at/525/1/RR-76-020.pdf Barceló-Vidal, C. and Martín-Fernández, J.A. (2016), The Mathematics of Compositional Analysis”, Austrian Journal of Statistics, 45(4), 57-71. DOI: http://dx.doi.org/10.17713/ajs.v45i4.142. Colignatus, Th. (2006), “On the sample distribution of the adjusted coefficient of determination (R2Adj) in OLS”, http://library.wolfram.com/infocenter/MathSource/6269/ Colignatus, Th. (2007), "Correlation and regression in contingency tables. A measure of association or correlation in nominal data (contingency tables), using determinants", https://mpra.ub.uni-muenchen.de/3660/ Colignatus, Th. (2009, 2015), “Elegance with substance”, https://zenodo.org/record/291974 Colignatus, Th. (2010), "Single vote multiple seatselections. Didactics of district versus proportional representation, using the examples of the United Kingdom and The Netherlands", https://mpra.ub.uni-muenchen.de/22782/ Colignatus, Th. (2011), "Conquest of the Plane", https://zenodo.org/record/291972 Colignatus, Th. (2017a), "Two conditions for the application of Lorenz curve and Gini coefficient to voting and allocated seats", https://mpra.ub.uni-muenchen.de/80297/ Colignatus, Th. (2017b), “Statistics, slope, cosine, sine, sign, significance and R-squared”, https://boycottholland.wordpress.com/2017/10/21/statistics-slope-cosine-sine-sign-significance-and-r-squared/ Colignatus, Th. (2017c), “Voting theory and the Brexit referendum question”, RES Newsletter 177, http://www.res.org.uk/view/art4Apr17Features.html Colignatus, Th. (2017d), “Great Britain's June 2017preferences on Brexit options”, RES Newsletter, October, 6-9, http://www.res.org.uk/view/art2Oct17Features.html Colignatus, Th. (2017e), “Dealing with denial: Cause and cure of Brexit”, https://boycottholland.wordpress.com/2017/12/01/dealing-with-denial-cause-and-cure-ofbrexit/ Colignatus, Th. (2018a), “Comparing the Aitchison distance and the angular distance for use as inequality or disproportionality measures for votes and seats”, https://mpra.ub.uni-muenchen.de/84387 also at https://www.wolframcloud.com/objects/thomas-cool/Voting/2018-01-18-Aitchison.nb Colignatus, Th. (2018b), “Measures of policy distance and inequality / disproportionality of votes and seats”, https://mpra.ub.uni-muenchen.de/84324/ also at https://www.wolframcloud.com/objects/thomas-cool/Voting/2018-02-02-PolicyDistance.nb Colignatus, Th. (2018c), "One woman, one vote. Though not in the USA, UK and France", first version in 2017 but updated in 2018, https://mpra.ub.uni-muenchen.de/84482/ Colignatus, Th. (2018d), “Comparing votes and seats with cosine, sine and sign, with attention for the slope and enhanced sensitivity to inequality / disproportionality”, first version in 2017 but updated in 2018, https://mpra.ub.unimuenchen.de/84469 Dongen, S. van & A.J. Enright (2012), "Metric distances derived from cosine similarity and Pearson and Spearman correlations", https://arxiv.org/abs/1208.3145 Egghe, L. and L. Leydesdorff (2009), “The relation between Pearson’s correlation coefficient r and Salton’s cosine measure”, J. of the Am. Soc. for Information Science and Technology, 60(5), p 1027-1036, http://hdl.handle.net/1942/8494 Eisenhauer, J.G. (2003), "Regression through the origin", Teaching Statistics. Volume 25, Number 3, Autumn 2003, p76-80 Ford, C. (2015), “Is R-squared Useless?”, http://data.library.virginia.edu/is-r-squared-useless/ Gallagher, M. (1991), "Proportionality, disproportionality and electoral systems", Electoral Studies, 10:1, 33-51, https://www.tcd.ie/Political_Science/draft/staff/michael_gallagher/ElectoralStudies1991.pdf Gelman, A. and G. King (1994), “A Unified Method of Evaluating Electoral Systems and Redistricting Plans”, American Journal of Political Science, 38, Pp. 514–554, https://gking.harvard.edu/files/abs/writeit-abs.shtml Gelman, A. (2007), “Significance testing in economics: McCloskey, Ziliak, Hoover, and Siegler”, http://andrewgelman.com/2007/10/05/significance_te/ Gelman, A. and H. Stern (2006), “The Difference Between “Significant” and “Not Significant” is not Itself Statistically Significant”, The American Statistician, November 2006, Vol. 60, No. 4, p328-331 Giles, D. (2013), “Unbiased Model Selection Using the Adjusted R-Squared”, http://davegiles.blogspot.nl/2013/08/unbiased-model-selection-using-adjusted.html (actually try http://davegiles.blogspot.nl/search?q=R-squared) Johnston, J. (1972), “Econometric methods”, McGraw-Hill Karpov, A. (2008), "Measurement of disproportionality in proportional representation systems", Mathematical and Computer Modelling, Volume 48, Issues 9–10, November 2008, Pages 1421-1438, http://www.sciencedirect.com/science/article/pii/S0895717708001933 Politics Koppel, M, and A. Diskin (2009), "Measuring disproportionality, volatility and malapportionment: axiomatization and solutions", Social Choice and Welfare, August, 33:281, https://www.researchgate.net/publication/225444815_Measuring_disproportionality_volatility_and_malapportionment_Axiomatization_and_solutions Kozak, A. and R. A. Kozak (1995), "Notes on regression through the origin", The Forestry Chronicle, May/June, Vol 71 no 3, p326-330 Lehmann, E.L. (2008), “On the history and use of some standard statistical models”, IMS Collections. Probability and Statistics: Essays in Honor of David A. Freedman, https://arxiv.org/abs/0805.2838 Mood, A. and F. Graybill (1963), “Introduction to the theory of statistics”, McGraw-Hill Patten, C. (2017), “What Brexit means for Britain’s future, according to Oxford University’s Chancellor”, https://blog.politics.ox.ac.uk/brexit-means-britains-future-according-oxford-universitys-chancellor/ Pearl, J. (2000), “Causality”, CUP Shalizi, C. (2015), “Lecture 10: F-Tests, R2, and Other Distractions”, (October 16), http://www.stat.cmu.edu/~cshalizi/mreg/15/lectures/10/lecture-10.pdf Shugart, M.S. & R. Taagepera (2017), “Votes from seats. Logical models of electoral systems”, CUP, https://doi.org/10.1017/9781108261128 Stigler, S. (2008), “Karl Pearson’s Theoretical Errors and the Advances They Inspired”, Statistical Science, Vol. 23, No. 2, 261–271, arXiv:0808.4032v1 Taagepera, R. and B. Grofman (2003), "Mapping the indices of seats-votes disproportionality and inter-election volatility", Party Politics, 9(6), p659-677, http://escholarship.org/uc/item/0m9912ff#page-1 Theil, H. (1971), “Principles of Econometrics”, Wiley UK Electoral Commission (2017a), “Voting in 2017. Understanding public attitudes towards elections and voting”, https://www.electoralcommission.org.uk/__data/assets/pdf_file/0011/234893/Voting-in-2017-Final.pdf UK Electoral Commission (2017b), “2017 UK general election results”, https://www.electoralcommission.org.uk/find-information-by-subject/elections-and-referendums/past-elections-and-referendums/uk-general-elections/2017-uk-general-election-results UK Electoral Commission (2017c), “UK Parliamentary General Election, June 2017”, https://www.electoralcommission.org.uk/__data/assets/pdf_file/0004/234976/UKPGE-2017-electoral-data-report.pdf see also the data files https://www.electoralcommission.org.uk/our-work/our-research/electoral-data/electoral-data-files-and-reports Varian, H. (2016), “Causal inference in economics and marketing”, July 5, 2016 vol. 113 no. 27, 7310-7315, http://www.pnas.org/content/113/27/7310.abstract Wilcox, R. (2017), “New statistical methods would let researchers deal with data in better, more robust ways”, Significance, May 9, https://www.significancemagazine.com/science/548-new-statistical-methods-would-let-researchers-deal-with-data-in-better-more-robust-ways Ziliak, S.T. and D.N. McCloskey (2007), “The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives”, Univ. of Michigan Press |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/84722 |
Available Versions of this Item
- An overview of the elementary statistics of correlation, R-squared, cosine, sine, and regression through the origin, with application to votes and seats for Parliament. (deposited 21 Feb 2018 05:26) [Currently Displayed]