QUANTITATIVE METHODS II Mid-Term Examination Monday‚ October22‚ 2012 Time : 150 minutes Total No. of Pages :17 Name ________________________ Total No. of Questions: 3 Roll No. ________________________ Total marks:35 Section: _______________________ Instructions 1. This is a Closed Book Exam. You are not allowed to carry anything other than stationary and calculator. 2. Answer all questions only in the space provided following the question. 3.
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Poisson Regression This page shows an example of poisson regression analysis with footnotes explaining the output. The data collected were academic information on 316 students. The response variable is days absent during the school year (daysabs)‚ from which we explore its relationship with math standardized tests score (mathnce)‚ language standardized tests score (langnce) and gender . As assumed for a Poisson model our response variable is a count variable and each subject has the same length
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1. Chi-square Goodness-of-fit Tests Jake is trying to invest his money in stock market‚ is not sure that he could earn a profit or lose his money when he invests to an AT&T company’s stock or a stock market index‚ Dow Jones Industry Average. So he called his friend who works at financial consulting company and heard that the monthly positive and negative investment returns on AT&T and Dow Jones Industry Average were historically almost the same. However the economic situation recently has been getting
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Quantitative Methods Project Regression Analysis for the pricing of players in the Indian Premier League Executive Summary The selling price of players at IPL auction is affected by more than one factor. Most of these factors affect each other and still others impact the selling price only indirectly. The challenge of performing a multiple regression analysis on more than 25 independent
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Limitations: Regression analysis is a commonly used tool for companies to make predictions based on certain variables. Even though it is very common there are still limitations that arise when producing the regression‚ which can skew the results. The Number of Variables: The first limitation that we noticed in our regression model is the number of variables that we used. The more companies that you have to compare the greater the chance your model will be significant. We have found that
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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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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 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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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 Programming History of linear programming goes back as far as 1940s. Main motivation for the need of linear programming goes back to the war time when they needed ways to solve many complex planning problems. The simplex method which is used to solve linear programming was developed by George B. Dantzig‚ in 1947. Dantzig‚ was one in who did a lot of work on linear programming‚ he was reconzied by several honours. Dantzig’s discovery was through his personal contribution‚ during WWII when Dantzig
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