QUADRATIC EQUATIONS Quadratic equations Any equation of the form ax2 + bx + c=0‚ where a‚b‚c are real numbers‚ a 0 is a quadratic equation. For example‚ 2x2 -3x+1=0 is quadratic equation in variable x. SOLVING A QUADRATIC EQUATION 1.Factorisation A real number a is said to be a root of the quadratic equation ax2 + bx + c=0‚ if aa2+ba+c=0. If we can factorise ax2 + bx + c=0‚ a 0‚ into a product of linear factors‚ then the roots of the quadratic equation ax2 + bx + c=0 can be found
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Chapter 13 Linear Regression and Correlation True/False 1. If a scatter diagram shows very little scatter about a straight line drawn through the plots‚ it indicates a rather weak correlation. Answer: False Difficulty: Easy Goal: 1 2. A scatter diagram is a chart that portrays the correlation between a dependent variable and an independent variable. Answer: True Difficulty: Easy Goal: 1 AACSB: AS 3. An economist is interested in predicting
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DIFFERENTIAL EQUATIONS 2.1 Separable Variables 2.2 Exact Equations 2.2.1 Equations Reducible to Exact Form. 2.3 Linear Equations 4. Solutions by Substitutions 2.4.1 Homogenous Equations 2.4.2 Bernoulli’s Equation 2.5 Exercises In this chapter we describe procedures for solving 4 types of differential equations of first order‚ namely‚ the class of differential equations of first order where variables x and y can be separated‚ the class of exact equations (equation
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Accounting is founded on the basic equation that states a company’s Assets equal their total Liabilities plus their total Owner’s Equity . This equation is summarized as ALOE . This isthe basis of the Balance Sheet.Assets are the company’s furniture‚ fixtures and equipment‚ physical property‚ intellectual property and other resources. These properties include the physical land as well as the equipmentand building improvements on the property.A company’s liabilities
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| | |Assignment title | | | | |Simultaneous Equation | | |Programme (e.g.: APDMS) |HND CSD | | |Unit
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Introduction to Linear Programming Steven J. Miller∗ March 31‚ 2007 Mathematics Department Brown University 151 Thayer Street Providence‚ RI 02912 Abstract We describe Linear Programming‚ an important generalization of Linear Algebra. Linear Programming is used to successfully model numerous real world situations‚ ranging from scheduling airline routes to shipping oil from refineries to cities to finding inexpensive diets capable of meeting the minimum daily requirements. In many of these problems‚ the number
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(2003) 1 OPERATIONS RESEARCH: 343 1. LINEAR PROGRAMMING 2. INTEGER PROGRAMMING 3. GAMES Books: Ð3Ñ IntroÞ to OR ÐF.Hillier & J. LiebermanÑ; Ð33Ñ OR ÐH. TahaÑ; Ð333Ñ IntroÞ to Mathematical Prog ÐF.Hillier & J. LiebermanÑ; Ð3@Ñ IntroÞ to OR ÐJ.Eckert & M. KupferschmidÑÞ LP (2003) 2 LINEAR PROGRAMMING (LP) LP is an optimal decision making tool in which the objective is a linear function and the constraints on the decision problem are linear equalities and inequalities. It is a very popular
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Uniform linear acceleration Introduction This topic is about particles which move in a straight line and accelerate uniformly. Problems can vary enormously‚ so you have to have your wits about you. Problems can be broken down into three main categories: Constant uniform acceleration Time-speed graphs Problems involving two particles Constant uniform acceleration Remember what the following variables represent: t = the time ; a = the acceleration ; u = the initial speed ; v = the final
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Physical Optics UNIT -I Chapter-1 One Dimensional Wave Equation Introduction Wave equation in one dimension Chapter-2 Three Dimensional Wave Equation Total energy of a vibrating particle Superposition of two waves acting along the same line Graphical methods of adding disturbances of the same frequency Chapter – 1 Introduction: The branch of Physics based on the wave concept of light is called ‘Wave Optics’ or ‘Physical Optics’. Mathematical representation of
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Z00_REND1011_11_SE_MOD7 PP2.QXD 2/21/11 12:39 PM Page 1 7 MODULE Linear Programming: The Simplex Method LEARNING OBJECTIVES After completing this chapter‚ students will be able to: 1. Convert LP constraints to equalities with slack‚ surplus‚ and artificial variables. 2. Set up and solve LP problems with simplex tableaus. 3. Interpret the meaning of every number in a simplex tableau. 4. Recognize special cases such as infeasibility‚ unboundedness and degeneracy. 5
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