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    Regression Analysis

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    Regression Analysis Exercises 1- A farmer wanted to find the relationship between the amount of fertilizer used and the yield of corn. He selected seven acres of his land on which he used different amounts of fertilizer to grow corn. The following table gives the amount (in pounds) of fertilizer used and the yield (in bushels) of corn for each of the seven acres. |Fertilizer Used |Yield of Corn | |120

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    Linear Programming

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    Duality in Linear Programming 4 In the preceding chapter on sensitivity analysis‚ we saw that the shadow-price interpretation of the optimal simplex multipliers is a very useful concept. First‚ these shadow prices give us directly the marginal worth of an additional unit of any of the resources. Second‚ when an activity is ‘‘priced out’’ using these shadow prices‚ the opportunity cost of allocating resources to that activity relative to other activities is determined. Duality in linear programming

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    Linear Equations

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    2014/9/16 Linear Equations Ad Options Ads by Vidx Linear Equations A linear equation is an  equation  for a straight line These are all linear equations: y = 2x+1 5x = 6+3y y/2 = 3 ­ x Let us look more closely at one example: Example: y = 2x+1 is a linear equation: The graph of y = 2x+1 is a straight line   When x increases‚ y increases twice as fast‚ hence 2x When x is 0‚ y is already 1. Hence +1 is also needed So: y = 2x + 1 Here are some example values: http://www.mathsisfun.com/algebra/linear-equations

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    MULTIPLE REGRESSION After completing this chapter‚ you should be able to: understand model building using multiple regression analysis apply multiple regression analysis to business decision-making situations analyze and interpret the computer output for a multiple regression model test the significance of the independent variables in a multiple regression model use variable transformations to model nonlinear relationships recognize potential problems in multiple

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    Linear Technologies

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    TO: Board of Directors‚ Linear Technologies FROM: Mr. Paul Coghlan CFO‚ Linear Technologies RE: Dividend Policy Summary: Based on the financials to date and the forward looking capital investments required Linear should increase their dividend payout by $0.01 per share. Entering the fourth quarter of 2003 the market seems to show continued signs of improvement. The company has shown steady growth and revenues are forecasted to exceed 2002’s by 19%. The forecast shows net income coming in

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    Linear Approaches

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    Linear Approaches Linear Approach is also known as the managerial approach because all the models that fall under this approach describe changes from the vision until the implementation stage. It is considered the simplest of all the traditional models in the theories of change. According to Stacey (1996) managing a change under any circumstances whether planned or unplanned is complex with many starts and stops throughout the complete process. This conclusion has been come to under the assumptions

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    CHAPTER 13 CORRELATION AND REGRESSION ANALYSIS OUTLINE 4.1 Definition of Correlation Analysis 4.2 Scatter Diagram and Types of Relationships 4.3 Correlation Coefficient 4.4 Interpretation of Correlation Coefficient 4.5 Definition of Regression Analysis 4.6 Dependent and Independent Variables 4.7 Simple Linear Regression: Least Squares Method 4.8 Using the simple Linear Regression equation 4.9 Cautionary Notes and Limitations OBJECTIVES By the end

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    linear programming

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    problems involve only two variables. For problems with more than two variables‚ we need to use complex techniques and tedious calculations to find the optimal solution. The spreadsheet and solver approach makes solving optimization problems a fairly simple task and it is more useful for students who do not have strong mathematics background. The first step is to organize the spreadsheet to represent the model. We use separate cells to represent decision variables‚ create a formula in a cell to represent

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    95-791 Spring 2013 Lecture #8 Predictive analytics: Regression Artur Dubrawski awd@cs.cmu.edu This unit • Good-old correlation scores revisited • Locally weighted regression – As an approximator of non-linear functions – As a framework for active/purposive acquisition of data 95-791 Data Mining Lecture #8 Slide 2 Copyright © 2000-2013 Artur Dubrawski Correlational scores of association between attributes of data • • • • Linear Rank Quadratic …. Would not it be great to have an

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    Cox Regression

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    Cox Regression Models Questions with Answers Worked Example An investigation is carried out into popularity of new cars being bought in the showroom of a Mercedes dealer. Data recorded for each car included colour‚ engine size and car type. A Cox proportional hazards model was fitted to the data and the results are given below: Write down the Cox hazard function according to this model. With regards to the model you have written down above state the following: • To which class of car does the

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