Reference no: EM131406102
Q1. The file P03_55.xlsx contains baseball data on all MLB teams from during the years 2004-2011 For each year and team, the total salary and the number of (regular-season) wins are listed.
a. Rearrange the data so that there are six columns: Team, Year, Salary Last Year, Salary This Year, Wins Last Year, and Wins This Year. You don't need rows for 2004 rows, because the data for 2003 isn't available for Salary Last Year and Wins Last Year. Your ending data set should have 7*30 rows of data.
b. Run a multiple regression for Wins This Year versus the other variables (besides Team). Then run a forward stepwise regression with these same variables. Compare the two equations, and explain exactly what the coefficients of the equation from the forward method imply about wins.
c. The Year variable should be insignificant. Is it? Why would it be contradictory for the 'true coefficient of Year to be anything other than zero?
d. Statistical inference from regression equations is all about inferring from the given data to a larger population. Does it make sense to talk about a larger population in this situation? If so, what is the larger population?
Q2. The file P11_40.xlsx contains monthly sales for a photography studio and the price charged per portrait during each month. Use regression to estimate an equation for predicting the current month's sales from last month's sales and the current month's price.
a. If the price of a portrait during month 21 is $30, predict month 21 sales.
b. Discuss how you can tell whether autocorrelation, multicollinearity, or heteroscedasticity might be a problem.
Attachment:- Assignment Files.rar
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