The Cauchy-Schwarz Inequality
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The Lorenz Curve
Charting Income Inequality The Lorenz Curve Resources for policy making Module 000 Charting Income Inequality The Lorenz Curve Resources for policy making Charting Income Inequality The Lorenz Curve by Lorenzo Giovanni Bellù, Agricultural Policy Support Service, Policy Assistance Division, FAO, Rome, Italy Paolo Liberati, University of Urbino, "Carlo Bo", Institute of Economics, Urbino, Italy for the Food and Agriculture Organization of the United Nations, FAO About EASYPol The EASYPol home page is available at: www.fao.org/easypol EASYPol is a multilingual repository of freely downloadable resources for policy making in agriculture, rural development and food security. The resources are the results of research and field work by policy experts at FAO. The site is maintained by FAO’s Policy Assistance Support Service, Policy and Programme Development Support Division, FAO. This modules is part of the resource package Analysis and monitoring of socio-economic impacts of policies. The designations employed and the presentation of the material in this information product do not imply the expression of any opinion whatsoever on the part of the Food and Agriculture Organization of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. © FAO November 2005: All rights reserved. Reproduction and dissemination of material contained on FAO's Web site for educational or other non-commercial purposes are authorized without any prior written permission from the copyright holders provided the source is fully acknowledged. Reproduction of material for resale or other commercial purposes is prohibited without the written permission of the copyright holders. -
Inequality Measurement Development Issues No
Development Strategy and Policy Analysis Unit w Development Policy and Analysis Division Department of Economic and Social Affairs Inequality Measurement Development Issues No. 2 21 October 2015 Comprehending the impact of policy changes on the distribu- tion of income first requires a good portrayal of that distribution. Summary There are various ways to accomplish this, including graphical and mathematical approaches that range from simplistic to more There are many measures of inequality that, when intricate methods. All of these can be used to provide a complete combined, provide nuance and depth to our understanding picture of the concentration of income, to compare and rank of how income is distributed. Choosing which measure to different income distributions, and to examine the implications use requires understanding the strengths and weaknesses of alternative policy options. of each, and how they can complement each other to An inequality measure is often a function that ascribes a value provide a complete picture. to a specific distribution of income in a way that allows direct and objective comparisons across different distributions. To do this, inequality measures should have certain properties and behave in a certain way given certain events. For example, moving $1 from the ratio of the area between the two curves (Lorenz curve and a richer person to a poorer person should lead to a lower level of 45-degree line) to the area beneath the 45-degree line. In the inequality. No single measure can satisfy all properties though, so figure above, it is equal to A/(A+B). A higher Gini coefficient the choice of one measure over others involves trade-offs. -
SOLVING ONE-VARIABLE INEQUALITIES 9.1.1 and 9.1.2
SOLVING ONE-VARIABLE INEQUALITIES 9.1.1 and 9.1.2 To solve an inequality in one variable, first change it to an equation (a mathematical sentence with an “=” sign) and then solve. Place the solution, called a “boundary point”, on a number line. This point separates the number line into two regions. The boundary point is included in the solution for situations that involve ≥ or ≤, and excluded from situations that involve strictly > or <. On the number line boundary points that are included in the solutions are shown with a solid filled-in circle and excluded solutions are shown with an open circle. Next, choose a number from within each region separated by the boundary point, and check if the number is true or false in the original inequality. If it is true, then every number in that region is a solution to the inequality. If it is false, then no number in that region is a solution to the inequality. For additional information, see the Math Notes boxes in Lessons 9.1.1 and 9.1.3. Example 1 3x − (x + 2) = 0 3x − x − 2 = 0 Solve: 3x – (x + 2) ≥ 0 Change to an equation and solve. 2x = 2 x = 1 Place the solution (boundary point) on the number line. Because x = 1 is also a x solution to the inequality (≥), we use a filled-in dot. Test x = 0 Test x = 3 Test a number on each side of the boundary 3⋅ 0 − 0 + 2 ≥ 0 3⋅ 3 − 3 + 2 ≥ 0 ( ) ( ) point in the original inequality. Highlight −2 ≥ 0 4 ≥ 0 the region containing numbers that make false true the inequality true. -
Stability of the Logarithmic Brunn-Minkowski Inequality
Stability of the Logarithmic Brunn-Minkowski inequality in the case of many hyperplane symmetries K´aroly J. B¨or¨oczky,∗† Apratim De‡ March 11, 2021 Dedicated to Prof. Erwin Lutwak on the occasion of his seventy-fifth birthday Abstract In the case of symmetries with respect to n independent linear hyperplanes, a stability versions of the Logarithmic Brunn-Minkowski inequality and the Logarithmic Minkowski inequality for convex bodies are established. MSC 52A40 1 Introduction The classical Brunn-Minkowski inequality form the core of various areas in probability, additive combinatorics and convex geometry (see Gardner [48], Schneider [83] and Tao, Vu [85]). For recent related work in the theory of arXiv:2101.02549v3 [math.MG] 10 Mar 2021 valuations, algorithmic theory and the Gaussian setting, see say Jochemko, Sanyal [60, 61], Kane [62], Gardner, Zvavitch [49], Eskenazis, Moschidis [37]. The rapidly developing new Lp-Brunn-Minkowski theory (where p = 1 is the classical case) initiated by Lutwak [68, 69, 70], has become main ∗Supported by NKFIH grant K 132002 †Alfr´ed R´enyi Institute of Mathematics, Realtanoda u. 13-15, H-1053 Budapest, Hun- gary, and Department of Mathematics, Central European University, Nador u. 9, H-1051, Budapest, Hungary, [email protected] ‡Department of Mathematics, Central European University, Nador u. 9, H-1051, Bu- dapest, Hungary, [email protected] 1 research area in modern convex geometry and geometric analysis. Following Firey [45] and Lutwak [68, 69, 70], major results have been obtained by Hug, Lutwak, Yang, Zhang [58], and more recently the papers Kolesnikov, Milman [65], Chen, Huang, Li, Liu [26], Hosle, Kolesnikov, Livshyts [57], Kolesnikov, Livshyts [64] present new developments and approaches. -
The FKG Inequality for Partially Ordered Algebras
J Theor Probab (2008) 21: 449–458 DOI 10.1007/s10959-007-0117-7 The FKG Inequality for Partially Ordered Algebras Siddhartha Sahi Received: 20 December 2006 / Revised: 14 June 2007 / Published online: 24 August 2007 © Springer Science+Business Media, LLC 2007 Abstract The FKG inequality asserts that for a distributive lattice with log- supermodular probability measure, any two increasing functions are positively corre- lated. In this paper we extend this result to functions with values in partially ordered algebras, such as algebras of matrices and polynomials. Keywords FKG inequality · Distributive lattice · Ahlswede-Daykin inequality · Correlation inequality · Partially ordered algebras 1 Introduction Let 2S be the lattice of all subsets of a finite set S, partially ordered by set inclusion. A function f : 2S → R is said to be increasing if f(α)− f(β) is positive for all β ⊆ α. (Here and elsewhere by a positive number we mean one which is ≥0.) Given a probability measure μ on 2S we define the expectation and covariance of functions by Eμ(f ) := μ(α)f (α), α∈2S Cμ(f, g) := Eμ(fg) − Eμ(f )Eμ(g). The FKG inequality [8]assertsiff,g are increasing, and μ satisfies μ(α ∪ β)μ(α ∩ β) ≥ μ(α)μ(β) for all α, β ⊆ S. (1) then one has Cμ(f, g) ≥ 0. This research was supported by an NSF grant. S. Sahi () Department of Mathematics, Rutgers University, New Brunswick, NJ 08903, USA e-mail: [email protected] 450 J Theor Probab (2008) 21: 449–458 A special case of this inequality was previously discovered by Harris [11] and used by him to establish lower bounds for the critical probability for percolation. -
On Isoperimetric Inequalities in Minkowski Spaces
Hindawi Publishing Corporation Journal of Inequalities and Applications Volume 2010, Article ID 697954, 18 pages doi:10.1155/2010/697954 Research Article On Isoperimetric Inequalities in Minkowski Spaces Horst Martini1 and Zokhrab Mustafaev2 1 Faculty of Mathematics, University of Technology Chemnitz, 09107 Chemnitz, Germany 2 Department of Mathematics, University of Houston-Clear Lake, Houston, TX 77058, USA Correspondence should be addressed to Horst Martini, [email protected] Received 11 July 2009; Revised 2 December 2009; Accepted 4 March 2010 Academic Editor: Ulrich Abel Copyright q 2010 H. Martini and Z. Mustafaev. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The purpose of this expository paper is to collect some mainly recent inequalities, conjectures, and open questions closely related to isoperimetric problems in real, finite-dimensional Banach spaces Minkowski spaces. We will also show that, in a way, Steiner symmetrization could be used as a useful tool to prove Petty’s conjectured projection inequality. 1. Introductory General Survey In Geometric Convexity, but also beyond its limits, isoperimetric inequalities have always played a central role. Applications of such inequalities can be found in Stochastic Geometry, Functional Analysis, Fourier Analysis, Mathematical Physics, Discrete Geometry, Integral Geometry, and various further mathematical disciplines. We will present a survey on isoperimetric inequalities in real, finite-dimensional Banach spaces, also called Minkowski spaces. In the introductory part a very general survey on this topic is given, where we refer to historically important papers and also to results from Euclidean geometry that are potential to be extended to Minkowski geometry,thatis,to the geometry of Minkowski spaces of dimension d ≥ 2. -
Inequality and Armed Conflict: Evidence and Data
Inequality and Armed Conflict: Evidence and Data AUTHORS: KARIM BAHGAT GRAY BARRETT KENDRA DUPUY SCOTT GATES SOLVEIG HILLESUND HÅVARD MOKLEIV NYGÅRD (PROJECT LEADER) SIRI AAS RUSTAD HÅVARD STRAND HENRIK URDAL GUDRUN ØSTBY April 12, 2017 Background report for the UN and World Bank Flagship study on development and conflict prevention Table of Contents 1 EXECUTIVE SUMMARY IV 2 INEQUALITY AND CONFLICT: THE STATE OF THE ART 1 VERTICAL INEQUALITY AND CONFLICT: INCONSISTENT EMPIRICAL FINDINGS 2 2.1.1 EARLY ROOTS OF THE INEQUALITY-CONFLICT DEBATE: CLASS AND REGIME TYPE 3 2.1.2 LAND INEQUALITY AS A CAUSE OF CONFLICT 3 2.1.3 ECONOMIC CHANGE AS A SALVE OR TRIGGER FOR CONFLICT 4 2.1.4 MIXED AND INCONCLUSIVE FINDINGS ON VERTICAL INEQUALITY AND CONFLICT 4 2.1.5 THE GREED-GRIEVANCE DEBATE 6 2.1.6 FROM VERTICAL TO HORIZONTAL INEQUALITY 9 HORIZONTAL INEQUALITIES AND CONFLICT 10 2.1.7 DEFINITIONS AND OVERVIEW OF THE HORIZONTAL INEQUALITY ARGUMENT 11 2.1.8 ECONOMIC INEQUALITY BETWEEN ETHNIC GROUPS 14 2.1.9 SOCIAL INEQUALITY BETWEEN ETHNIC GROUPS 18 2.1.10 POLITICAL INEQUALITY BETWEEN ETHNIC GROUPS 19 2.1.11 OTHER GROUP-IDENTIFIERS 21 2.1.12 SPATIAL INEQUALITY 22 CONTEXTUAL FACTORS 23 WITHIN-GROUP INEQUALITY 26 THE CHALLENGE OF CAUSALITY 27 CONCLUSION 32 3 FROM OBJECTIVE TO PERCEIVED HORIZONTAL INEQUALITIES: WHAT DO WE KNOW? 35 INTRODUCTION 35 LITERATURE REVIEW 35 3.1.1 DO PERCEIVED INEQUALITIES INCREASE THE RISK OF CONFLICT? MEASUREMENT AND FINDINGS 37 3.1.2 DO OBJECTIVE AND PERCEIVED INEQUALITIES OVERLAP? MISPERCEPTIONS AND MANIPULATION 41 3.1.3 DO PERCEPTIONS -
Solving Linear Inequalities
Solving Linear Inequalities Farah Dawood Some Application of Inequalities Inequalities are used more often in real life than equalities: ❖ Businesses use inequalities to control inventory, plan production lines, produce pricing models, and for shipping. ❖ Linear programming is a branch of mathematics that uses systems of lin e a r in e q u a litie s to solve re a l-world problems. ❖ Financial occupations often require the use of linear inequalities such as accountants, auditors, budget analysts and insurance underwriters to determine pricing and set budgets. Inequality Symbols What is a linear Inequality ? ● Linear inequality is an inequality which involves a linear function (with first power). ● Linear inequality contains one of the symbols of inequality ● The solution of a linear inequality in two variable like Ax+By>C is an ordered pair (x,y) that make an inequality true. Solving Linear Inequalities For One Variable ` ● Solve the inequality as you would an equation which means that "whatever you do to one side, you must do to the other side". ● If you multiply or divide by a negative number, REVERSE the inequality symbol. ● We can write the answer in interval notation. Steps for Graphing Solution on Number Line ● Use an open circle on the graph if your inequality symbol is greater than or less than. ● Use a closed circle on the graph if your inequality symbol is greater than or equal to OR less than or equal to. ● Arrow will point to the left if the inequality symbol is less than. ● Arrow will point to the right if the inequality symbol is greater than. -
Inequalities in the European Union—A Partial Order Analysis of the Main Indicators
sustainability Article Inequalities in the European Union—A Partial Order Analysis of the Main Indicators Lars Carlsen 1,* and Rainer Bruggemann 2 1 Awareness Center, Linkøpingvej 35, Trekroner, DK-4000 Roskilde, Denmark 2 Department of Ecohydrology, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Oskar—Kösters-Str. 11, D-92421 Schwandorf, Germany; [email protected] * Correspondence: [email protected] Abstract: The inequality within the 27 European member states has been studied. Six indicators proclaimed by Eurostat to be the main indicators charactere the countries: (i) the relative median at-risk-of-poverty gap, (ii) the income distribution, (iii) the income share of the bottom 40% of the population, (iv) the purchasing power adjusted GDP per capita, (v) the adjusted gross disposable income of households per capita and (vi) the asylum applications by state of procedure. The resulting multi-indicator system was analyzed applying partial ordering methodology, i.e., including all indicators simultaneously without any pretreatment. The degree of inequality was studied for the years 2010, 2015 and 2019. The EU member states were partially ordered and ranked. For all three years Luxembourg, The Netherlands, Austria, and Finland are found to be highly ranked, i.e., having rather low inequality. Bulgaria and Romania are, on the other hand, for all three years ranked low, with the highest degree of inequality. Excluding the asylum indicator, the risk-poverty-gap and the adjusted gross disposable income were found as the most important indicators. If, however, the asylum application is included, this indicator turns out as the most important for the mutual Citation: Carlsen, L.; Bruggemann, R. -
Mapping Recent Inequality Trends in Developing Countries
Mapping recent inequality trends in developing countries Rebecca Simson Working paper 24 May 2018 III Working paper 24 Rebecca Simson LSE International Inequalities Institute The International Inequalities Institute (III) based at the London School of Economics and Political Science (LSE) aims to be the world’s leading centre for interdisciplinary research on inequalities and create real impact through policy solutions that tackle the issue. The Institute provides a genuinely interdisciplinary forum unlike any other, bringing together expertise from across the School and drawing on the thinking of experts from every continent across the globe to produce high quality research and innovation in the field of inequalities. In addition to our working papers series all these publications are available to download free from our website: www.lse.ac.uk/III For further information on the work of the Institute, please contact the Institute Manager, Liza Ryan at [email protected] International Inequalities Institute The London School of Economics and Political Science Houghton Street London WC2A 2AE Email: [email protected] Web site: www.lse.ac.uk/III @LSEInequalities © Rebecca Simson. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including ã notice, is given to the source. 2 III Working paper 24 Rebecca Simson Editorial note and acknowledgements This paper was written with the engagement and input of the project research committee: Mike Savage, Beverley Skeggs, Rana Zincir-Celal, Duncan Green, Paul Segal and Pedro Mendes Loureiro. Students from the LSE M.Sc. course, ‘Social Scientific Analysis of Inequalities’, also provided a wealth of useful inputs to this study. -
Week 4 – Complex Numbers
Week 4 – Complex Numbers Richard Earl∗ Mathematical Institute, Oxford, OX1 2LB, November 2003 Abstract Cartesian and polar form of a complex number. The Argand diagram. Roots of unity. The relation- ship between exponential and trigonometric functions. The geometry of the Argand diagram. 1 The Need For Complex Numbers All of you will know that the two roots of the quadratic equation ax2 + bx + c =0 are b √b2 4ac x = − ± − (1) 2a and solving quadratic equations is something that mathematicians have been able to do since the time of the Babylonians. When b2 4ac > 0 then these two roots are real and distinct; graphically they are where the curve y = ax2 + bx−+ c cuts the x-axis. When b2 4ac =0then we have one real root and the curve just touches the x-axis here. But what happens when− b2 4ac < 0? Then there are no real solutions to the equation as no real squares to give the negative b2 − 4ac. From the graphical point of view the curve y = ax2 + bx + c lies entirely above or below the x-axis.− 3 4 4 3.5 2 3 3 2.5 1 2 2 1.5 1 1 -1 1 2 3 0.5 -1 -1 1 2 3 -1 1 2 3 Distinct real roots Repeated real root Complex roots It is only comparatively recently that mathematicians have been comfortable with these roots when b2 4ac < 0. During the Renaissance the quadratic would have been considered unsolvable or its roots would− have been called imaginary. (The term ‘imaginary’ was first used by the French Mathematician René Descartes (1596-1650). -
Inequalities and Their Measurement
IZA DP No. 1219 Inequalities and Their Measurement Almas Heshmati DISCUSSION PAPER SERIES DISCUSSION PAPER July 2004 Forschungsinstitut zur Zukunft der Arbeit Institute for the Study of Labor Inequalities and Their Measurement Almas Heshmati MTT Economic Research and IZA Bonn Discussion Paper No. 1219 July 2004 IZA P.O. Box 7240 53072 Bonn Germany Phone: +49-228-3894-0 Fax: +49-228-3894-180 Email: [email protected] Any opinions expressed here are those of the author(s) and not those of the institute. Research disseminated by IZA may include views on policy, but the institute itself takes no institutional policy positions. The Institute for the Study of Labor (IZA) in Bonn is a local and virtual international research center and a place of communication between science, politics and business. IZA is an independent nonprofit company supported by Deutsche Post World Net. The center is associated with the University of Bonn and offers a stimulating research environment through its research networks, research support, and visitors and doctoral programs. IZA engages in (i) original and internationally competitive research in all fields of labor economics, (ii) development of policy concepts, and (iii) dissemination of research results and concepts to the interested public. IZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available on the IZA website (www.iza.org) or directly from the author. IZA Discussion Paper No. 1219 July 2004 ABSTRACT Inequalities and Their Measurement This paper is a review of the recent advances in the measurement of inequality.