Expressions, Equations, and Inequalities
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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. -
Operations with Algebraic Expressions: Addition and Subtraction of Monomials
Operations with Algebraic Expressions: Addition and Subtraction of Monomials A monomial is an algebraic expression that consists of one term. Two or more monomials can be added or subtracted only if they are LIKE TERMS. Like terms are terms that have exactly the SAME variables and exponents on those variables. The coefficients on like terms may be different. Example: 7x2y5 and -2x2y5 These are like terms since both terms have the same variables and the same exponents on those variables. 7x2y5 and -2x3y5 These are NOT like terms since the exponents on x are different. Note: the order that the variables are written in does NOT matter. The different variables and the coefficient in a term are multiplied together and the order of multiplication does NOT matter (For example, 2 x 3 gives the same product as 3 x 2). Example: 8a3bc5 is the same term as 8c5a3b. To prove this, evaluate both terms when a = 2, b = 3 and c = 1. 8a3bc5 = 8(2)3(3)(1)5 = 8(8)(3)(1) = 192 8c5a3b = 8(1)5(2)3(3) = 8(1)(8)(3) = 192 As shown, both terms are equal to 192. To add two or more monomials that are like terms, add the coefficients; keep the variables and exponents on the variables the same. To subtract two or more monomials that are like terms, subtract the coefficients; keep the variables and exponents on the variables the same. Addition and Subtraction of Monomials Example 1: Add 9xy2 and −8xy2 9xy2 + (−8xy2) = [9 + (−8)] xy2 Add the coefficients. Keep the variables and exponents = 1xy2 on the variables the same. -
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. -
Algebraic Expressions 25
Section P.3 Algebraic Expressions 25 P.3 Algebraic Expressions What you should learn: Algebraic Expressions •How to identify the terms and coefficients of algebraic A basic characteristic of algebra is the use of letters (or combinations of letters) expressions to represent numbers. The letters used to represent the numbers are variables, and •How to identify the properties of combinations of letters and numbers are algebraic expressions. Here are a few algebra examples. •How to apply the properties of exponents to simplify algebraic x 3x, x ϩ 2, , 2x Ϫ 3y expressions x2 ϩ 1 •How to simplify algebraic expressions by combining like terms and removing symbols Definition of Algebraic Expression of grouping A collection of letters (called variables) and real numbers (called constants) •How to evaluate algebraic expressions combined using the operations of addition, subtraction, multiplication, divi- sion and exponentiation is called an algebraic expression. Why you should learn it: Algebraic expressions can help The terms of an algebraic expression are those parts that are separated by you construct tables of values. addition. For example, the algebraic expression x2 Ϫ 3x ϩ 6 has three terms: x2, For instance, in Example 14 on Ϫ Ϫ page 33, you can determine the 3x, and 6. Note that 3x is a term, rather than 3x, because hourly wages of miners using an x2 Ϫ 3x ϩ 6 ϭ x2 ϩ ͑Ϫ3x͒ ϩ 6. Think of subtraction as a form of addition. expression and a table of values. The terms x2 and Ϫ3x are called the variable terms of the expression, and 6 is called the constant term of the expression. -
Algebraic Expression Meaning and Examples
Algebraic Expression Meaning And Examples Unstrung Derrin reinfuses priggishly while Aamir always euhemerising his jugginses rousts unorthodoxly, he derogate so heretofore. Exterminatory and Thessalonian Carmine squilgeed her feudalist inhalants shrouds and quizzings contemptuously. Schizogenous Ransom polarizing hottest and geocentrically, she sad her abysm fightings incommutably. Do we must be restricted or subtracted is set towards the examples and algebraic expression consisting two terms in using the introduction and value Why would you spend time in class working on substitution? The most obvious feature of algebra is the use of special notation. An algebraic expression may consist of one or more terms added or subtracted. It is not written in the order it is read. Now we look at the inner set of brackets and follow the order of operations within this set of brackets. Every algebraic equations which the cube is from an algebraic expression of terms can be closed curve whose vertices are written. Capable an expression two terms at splashlearn is the first term in the other a variable, they contain variables. There is a wide variety of word phrases that translate into sums. Evaluate each of the following. The factor of a number is a number that divides that number exactly. Why do I have to complete a CAPTCHA? Composed of the pedal triangle a polynomial an consisting two terms or set of one or a visit, and distributivity of an expression exists but it! The first thing to note is that in algebra we use letters as well as numbers. Proceeding with the requested move may negatively impact site navigation and SEO. -
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. -
December 4, 2017 COURSE
MASTER COURSE OUTLINE Prepared By: Salah Abed, Tyler Wallace, Barbara Whitney, Brinn Harberts Date: December 4, 2017 COURSE TITLE Intermediate Algebra I GENERAL COURSE INFORMATION Dept.: MATH Course Num: 098 (Formerly: MPC 095, 096) CIP Code: 33.0101 Intent Code: 11 Program Code: Credits: 5 Total Contact Hrs Per Qtr.: 55 Lecture Hrs: 55 Lab Hrs: 0 Other Hrs: 0 Distribution Designation: None COURSE DESCRIPTION (as it will appear in the catalog) This course includes the study of intermediate algebraic operations and concepts, and the structure and use of algebra. This includes solving, graphing, and solving applications of linear equations and systems of equations; simplifying, factoring, and solving quadratic functions, introduction to functions and models; and exponential and logarithmic functions along with applications. Students cannot earn credit for both MAP 119 and Math 098. PREREQUISITES MATH 094 or placement TEXTBOOK GUIDELINES Appropriate text chosen by math faculty. COURSE LEARNING OUTCOMES Upon successful completion of the course, students should be able to demonstrate the following knowledge or skills: 1. Use order of operations to simplify expressions and solve algebraic equations. 2. Use given points or a graph to find the slope of a line and write its equation. 3. Apply various techniques to factor algebraic expressions. 4. Convert word problems to algebraic sentences when solving application problems. 5. Use factoring techniques, the square root method, and the quadratic formula to solve problems with quadratics. 6. Solve systems of linear equations using substitution and elimination methods. 7. Evaluate an expression given in function notation. 8. Use properties of exponents and logarithms to solve simple exponential equations and simplify expressions. -
The Cauchy-Schwarz Inequality
The Cauchy-Schwarz Inequality Proofs and applications in various spaces Cauchy-Schwarz olikhet Bevis och tillämpningar i olika rum Thomas Wigren Faculty of Technology and Science Mathematics, Bachelor Degree Project 15.0 ECTS Credits Supervisor: Prof. Mohammad Sal Moslehian Examiner: Niclas Bernhoff October 2015 THE CAUCHY-SCHWARZ INEQUALITY THOMAS WIGREN Abstract. We give some background information about the Cauchy-Schwarz inequality including its history. We then continue by providing a number of proofs for the inequality in its classical form using various proof tech- niques, including proofs without words. Next we build up the theory of inner product spaces from metric and normed spaces and show applications of the Cauchy-Schwarz inequality in each content, including the triangle inequality, Minkowski's inequality and H¨older'sinequality. In the final part we present a few problems with solutions, some proved by the author and some by others. 2010 Mathematics Subject Classification. 26D15. Key words and phrases. Cauchy-Schwarz inequality, mathematical induction, triangle in- equality, Pythagorean theorem, arithmetic-geometric means inequality, inner product space. 1 2 THOMAS WIGREN 1. Table of contents Contents 1. Table of contents2 2. Introduction3 3. Historical perspectives4 4. Some proofs of the C-S inequality5 4.1. C-S inequality for real numbers5 4.2. C-S inequality for complex numbers 14 4.3. Proofs without words 15 5. C-S inequality in various spaces 19 6. Problems involving the C-S inequality 29 References 34 CAUCHY-SCHWARZ INEQUALITY 3 2. Introduction The Cauchy-Schwarz inequality may be regarded as one of the most impor- tant inequalities in mathematics. -
Intermediate Algebra
Intermediate Algebra Gregg Waterman Oregon Institute of Technology c 2017 Gregg Waterman This work is licensed under the Creative Commons Attribution 4.0 International license. The essence of the license is that You are free to: • Share - copy and redistribute the material in any medium or format • Adapt - remix, transform, and build upon the material for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: • Attribution - You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. No additional restrictions ? You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits. Notices: You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation. No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material. For any reuse or distribution, you must make clear to others the license terms of this work. The best way to do this is with a link to the web page below. To view a full copy of this license, visit https://creativecommons.org/licenses/by/4.0/legalcode. Contents 1 Expressions and Exponents 3 1.1 Exponents .................................... -
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. -
Chapter 3. Mathematical Tools
Chapter 3. Mathematical Tools 3.1. The Queen of the Sciences We makenoapology for the mathematics used in chemistry.After all, that is what clas- sifies chemistry as a physical science,the grand goal of which is to reduce all knowledge to the smallest number of general statements.1 In the sense that mathematics is logical and solv- able, it forms one of the most precise and efficient languages to express concepts. Once a problem can be reduced to a mathematical statement, obtaining the desired result should be an automatic process. Thus, many of the algorithms of chemistry aremathematical opera- tions.This includes extracting parameters from graphical data and solving mathematical equations for ‘‘unknown’’quantities. On the other hand we have sympathyfor those who struggle with mathematical state- ments and manipulations. This may be in some measure due to the degree that mathematics isn’ttaught as algorithmic processes, procedures producing practical results. Formany, a chemistry course may be the first time theyhav e been asked to apply the mathematical tech- niques theylearned in school to practical problems. An important point to realize in begin- ning chemistry is that most mathematical needs are limited to arithmetic and basic algebra.2 The difficulties lie in the realm of recognition of the point at which an application crosses the 1 Physical science is not a misnomer; chemistry owes more to physics than physics owes to chemistry.Many believe there is only one algorithm of chemistry.Itisthe mathematical wav e equation first published in 1925 by the physicist Erwin Schr"odinger.Howev eritisavery difficult equation from which to extract chemical infor- mation. -
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