"Regression model in car industry" Essays and Research Papers

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    Regression with Discrete Dependent Variable CE 601 Term Project By Classification Type of Discrete Dependent Variable Example Problems Type of Regression Model Binary 1. Consumer economics 2. Decision to vote Logistic Regression Probit Regression Ordinal 1. Opinion survey 2. Rating systems Ordered Logistic Regression Ordered Probit Regression Nominal 1. Occupation choice 2. Blood type Multinomial Logistic Regression Count 1. Consumer demand 2

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    Michael Porter’s Five Forces Model is a model used to analyze a particular environment of an industry. An industry is a group of firms that market products which are close substitutes for each other‚ such as the automobile industry. According to Porter‚ there are five forces that determine an industry’s long-run profitability and attractiveness. These five competitive forces are the threat of entry of new competitors‚ or new entrants; the threat of substitutes; the bargaining power of buyers; the

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    growth of the economy and the high purchasing power of its population have made Malaysia the largest passenger car market in ASEAN. At the same time‚ the establishment of national car projects‚ PROTON and PERODUA‚ has transformed Malaysia from a mere motor car assembler into a car manufacturer. With a ratio of 200 cars for every one thousand people‚ Malaysia ranks among countries with high car ownership ratio in the region. Toyota‚ Honda‚ Nissan‚ Mercedes Benz‚ Volvo‚ BMW‚ Peugeot and Volkswagen are

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    CHAPTER I The Problem and Its Background Introduction Car loan is one of the consumer’s credits that are applied for personal use of a vehicle. This is usually unsecured and it is based on the borrower’s ability to pay. Most consumers need financing or leasing to acquire a vehicle. This paper explores how the defaulted consumer car loan affects the Philippines Automotive Industry. Base on Esquire Financing Incorporation‚ they seek the five C’s of credit from their borrowers which are character

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    Porters Five Forces Model & the Airline Industry Robert Warren 6/11/2011 Abstract Having conducted research on Porter’s Five Forces Model and the current business climate of the airline industry‚ I will be analyzing the industry using the Five Forces Model. Porter’s Five Forces model is a highly recognized framework for the analysis of business strategy. Five forces are derived from the model that attempts to determine the competitive intensity‚ competitive environment and overall

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    Porter’s Five Forces Model of Industry Structure An industry is a group of firms that market products which are close substitutes for each other (e.g. car industry‚ travel industry). Some industries are more profitable than others. Why? The answer lies in understanding the dynamics of competitive structure in an industry. The most influential analytical model for assessing the nature of competition in an industry is Michael Porter’s Five Forces Model‚ which is described below: Porter explains

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    STA9708 Regression Analysis: Literacy rates and Poverty rates As we are aware‚ poverty rate serve as an indicator for a number of causes in the world. Poverty rates are linked with infant mortality‚ education‚ child labor and crime etc. In this project‚ I will apply the regression analysis learned in the Statistics course to study the relationship between literacy rates and poverty rates among different states in USA. In my study‚ the poverty rates will be the independent variable (x) and literacy

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    relationship between CREDIT BALANCE and SIZE 2591+ 403.221 Determine the coefficient of correlation. Interpret. .75/ r-sq(56.6%). There is a mild correlation. Determine the coefficient of determination. Interpret. 56.6% Test the utility of this regression model (use a two tail test with α =.05). Interpret your results‚ including the p-value. P-value=0. Reject the null hpothesis. T value 7.9147 Based on your findings in 1-5‚ what is your opinion about using SIZE to predict CREDIT BALANCE? Size is

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    5645 | 3.17 | 32.11 | 2010 | 4284 | 3.28 | 31.23 | 2011 | 3674 | 2.65 | 24.16 | Using regression analysis we want to determine the relationship between ROA‚ ROE and stock price of PT BCA Tbk. In this case‚ ROA and ROE are the independent or explanatory variable (X)‚ while stock price is the dependent variable that we want to explain (Y). Regression Analysis SUMMARY OUTPUT | | | Regression Statistics | Multiple R | 0.13028475 | R Square | 0.016974116 | Adjusted R Square | -0

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    Javier Jorge Dr. Moss Managerial Analysis April 11th‚ 2012 Project 3 We are given a linear regression that gives us an equation on the relationship of Quantity on Total Cost. As stated in the project‚ the regression data is very good with a relatively high R2‚ significant F‚ and t-values but we can’t use this model to estimate plant size. When we perform a simple eye test on the residual plot for Q a trend seems to form from positive to negative and back to positive. When we also

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