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    Microsoft Excel Problems

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    Excel Problems 1. The following time series represent the total population of the United States‚ in thousands‚ over the last 12 years. |Year |Population (in 000‚s) | |1991 |253‚493 | |1992 |256‚894 | |1993 |260‚255 | |1994 |263‚436 | |1995 |266‚557 | |1996 |269‚667 | |1997 |272‚912

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    CHAPTER ONE: INTRODUCTION 1.1 Introduction Working capital is an important issue during financial decision making since it is being a part of investment in asset that requires appropriate financing investment (Zariyawati et al‚ 2009). However it is always being ignored by companies because it is related to short term period. The companies or managers should understand that items or transactions in short term period may give significant impact in future if the responsible managers does not

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    Term Project Report: The effect of unemployment of crime Table of Contents Background 3-4 Regression Analysis 5-6 Conclusion 7 References 8 Data 9 What affects do the unemployment rates have on crime level? 1. Purpose Statement The purpose of this project is to determine how the rate of criminal activity (CRIME) is affected by the rate of unemployment (UNEMP)‚ while also considering the affects of the fluctuation of Consumer Price Index

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    semi-vegetarians. The present study tries to use regression technique of demad forecasting to estimate the demand fuction of eggs for Raigarh district of Chhatisgarh for various occupational groups in rural and urban areas. In this study we consider variables like size and composition of family‚ family income‚ occupation‚ number of earning members etc. Likewise for soaps we choose variables like growth in population and increase in per capita income for regression. Demand Forecasting for Eggs: Eggs are

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    regular flow. • Briefly outline the forecastng technique(s) used by the company. Coca-Cola uses the forecasting technique of linear regression using a functional relationship between two or more correlated variables. The relationship is usually developed from observable data and plotted in a graph the two variables regress to form a straight line.The linear regression line is of the form Y=a+bX‚ where Y is the value of the dependent variable that we are solving for‚a is the Y-intercept‚ b is the slope

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    Homework 1

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    Chávez A01530382 Oscar Daniel Lechuga Pérez A01530442 José Ricardo Reyes A00454161 Problem 1 Explore the relationship between the selling prices (Y) and the appraised values (X) of the 150 homes in the file hw1_1.xlsx by estimating simple linear regression model. Also‚ compute the standard error of estimate se and the coefficient of determination R2 for the estimated least squares line. Interpret these measures and the least squares line for these data. a Is there evidence of a linear relationship

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    Pilgrim Bank

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    Part 1 Alan Green needs to answer the decision problem of whether charging fees for online banking use is more profitable for Pilgrim Bank than offering incentives to promote wider use of the online channel. To begin solving the problem‚ Mr. Green first must address the following research issues: how much more/less profit do online users generate; is this difference significant‚ what are the measures of customer profitability‚ what are the characteristic of the bank’s online users and profitable

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    of the companies listed in sensex really explains the value accretion for the shareholders and cause fluctuation in sensex. So‚ I have taken these variables as Independent variables and MVA as a dependent Variable (shareholders’ value) to apply regression analysis to come out with a result that which variable is having a high degree of Correlation with MVA and significantly explains variation in MVA. To perform this analysis secondary data has been collected from Prowess and www.bseindia.com

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    Real Estate Data Set

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    give an educated guess on a linear regression model for pricing real estate using a real facts date set using numbers and facts. Normally two approaches are used for valuing a real estate property: income and sales comparison. The sales assessment approach values a real estate property based on sale prices of similar properties. In this case the properties with familiar individuality are basically on the same price level‚ it would be typical to use a linear regression model to complete this demonstration

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    Long term energy consumption forecasting using genetic programming. Mathematical and Computational Applications‚ Vol. 13‚ No. 2‚ pp. 71-80. Bianco‚ V.‚ Manca‚ O.‚ & Nardini‚ S. (2009). Electricity consumption forecasting in Italy using linear regression models. Elsevier Ltd. Energy 34 (2009) 1413-1421. Mohamed‚ Z. & Bodger‚ P. (2003). Forecasting electricity consumption in New Zealand using economic and demographic variables. Elsevier Ltd. Energy 50 (2004) 1833-1843.

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