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Saint GBA334 module 3 assignment




Question;For this module, you will;complete the following problems from the textbook;? Chapter 4, pages 146-147;Problems 30, 31, and 32 using the Data Analysis;Add-In for Microsoft Excel;? Chapter 5, pages 188-189;Problems 25 and 31 using either Excel?s Data;Analysis Add-In or Excel QM;Chap 3#30 pg 146 A sample of nine public;universities and nine private universities wastaken. The total cost for the;year (including room and board) and the median SAT score (maximum total is;2400) at each school were recorded. It was felt that schools with higher median;SAT scores would have a better reputation and would charge more tuition as a;result of that. The data is in the table below. Use regression to help answer;the following questions based on this sample data. Do schools with higher SAT;scores charge more in tuition and fees? Are private schools more expensive than;public schools when SAT scores are taken into consideration? Discuss how;accurate you believe these results are using information related the regression;models.;Category Total Cost Median;SAT;Public 21,700 1990;Public 15,600 1620;Public 16,900 1810;Public 15,400 1540;Public 23,100 1540;Public 21,400 1600;Public 16,500 1560;Public 23,500 1890;Public 20,200 1620;Private 30,400 1630;Private 41,500 1840;Private 36,100 1980;Private 42,100 1930;Private 27,100 2130;Private 34,800 2010;Private 32,100 1590;Private 31,800 1720;Private 32,100 1770;# 31 pg 146;In 2008, the total payroll;for the New York Yankees was $209.1 million, while the total payroll for the;Tampa By Rays was about $43.8 million about 1/5th of that of the Yankees. The;table below lists the payrolls in millions for all 14 MLB teams in the American;league and the total victories for 2008;Team Payroll millions;victories;NY Yankees 209.1 89;Detroit Tigers 138.7 74;Boston Red Sox 133.4 95;Chicago White sox 121.2 89;Cleveland Indians 79 81;Baltimore Orioles 67.2 68;Oakland Athletics 48 75;Los Angeles Angels 119.2;100;Seattle Mariners 118 61;Toronto Blue Jays 98.6 86;Minnesota Twins 62.2 88;Kansas City 58.2 75;Tampa Bay 43.8 97;Texas Rangers 68.2 79;Develop a regression model;to predict total number of victories based on payroll of the team. Based on;results discuss how accurate the model is. Use the model to predict the number;of victories for a team with a payroll of $79million;#32;In 2009, the New York;Yankees won 103 baseball games during the regular season. The table on the next;page lists the number of victories (W), the earned-run- average (ERA), and the;batting average (AVG) of each team in the American League. The ERA is one;measure of the effectiveness of the pitching staff, and a lower number is *****;The batting average is one measure of effectiveness of the hitters, and a;higher number is *****;TEAM W ERA AVG;New York Yankees 103 4.26;0.283;Los Angeles Angels 97 4.45;0.285;Boston Red Sox 95 4.35 0.27;Minnesota Twins 87 4.5;0.274;Texas Rangers 87 4.38 0.26;Detroit Tigers 86 4.29 0.26;Seaattle Mariners 85 3.87;0.258;Tampa Bay Rays 84 4.33;0.263;Chicago White Sox 79 4.14;0.258;Toronto Blue Jays 75 4.47;0.266;Oakland Athletics 75 4.26;0.262;Cleveland Indians 65 5.06;0.264;Kansas City Royals 65 4.83;0.259;Baltimore Orioles 64 5.15;0.268;A.Develop a regression;model that could be used to predict the number of victories based on the ERA.;B.Develop a regression;model that could be used to predict the number of victories based on the;batting average.;C.Which of the two models;is better for predicting the number of victories?;D.Develop a multiple;regression model that includes both ERA and batting average. How does this;compare to the previous models?;Q5.25;Sales of industrial vacuum;cleaners at R. Lowenthal Supply Co. over the past 13 months are as follows;Sales (1,000s) MONTH Sales (1,000s) MONTH;11 January 14;August;14 February 17 September;16 March 12 October;10 April 14 November;15 May 16 December;17 June 11 January;11 July;(a) Using a moving average;with three periods, determine the demand for vacuum cleaners for next February.;(b) Using a weighted moving;average with three periods, determine the demand for vacuum cleans for;February. Use 3, 2 and 1 for the weights of the most recent, second most;recent, and third most recent periods, respectively. For example, if you were;forecasting the demand for February, November would have a weight of 1;December would have a weight of 2, and January would have a weight of 3.;(c) Evaluate the accuracy;of each of these methods.;(d) What other factors;might R. Lowenthal consider in forecasting sales?;#31 pg 189;A major source of revenue;in Texas is a state sales tax on certain;types of goods and;services. Data are compiled and the;state;comptroller uses them to;project future revenues for the state budget.;One particular category of goods is classified;as Retail Trade. Four;years of quarterly data for;one particular area of southeast Texas;follows;quarter year 1 year 2 year 3 year 4;------------------------------------------------------------;1 218 225 234 250;2 247 254 265 283;3 243 255 264 289;4 292 299 327 356;a)compute seasonal indices;for each quarter based on a CMA.;b)Deseasonalize the data;and develop a trend line on the deseasonalized;data.;c)Use the trend line to;forecast the sales for each quarter of year 5.;d)Use the seasonal indices;to adjust the forecasts found in part (c);to obtain the final;forecasts.


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