statistics homework 4.docx

# statistics homework 4.docx - HOMEWORK 4 A cost accountant...

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HOMEWORK 4 - A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch), production plant (Kingsland, and Yorktown), and production shift (day, and evening). The response variable in this model is ______. total cost - A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch), production plant (Kingsland, and Yorktown), and production shift (day, and evening). In this model, "shift" is ______. an independent variable - A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch), production plant (Kingsland, and Yorktown), and production shift (day, and evening). In this model, "batch size" is ______. an independent variable - A market analyst is developing a regression model to predict monthly household expenditures on groceries as a function of family size, household income, and household neighborhood (urban, suburban, and rural). The response variable in this model is _____. expenditures on groceries - A market analyst is developing a regression model to predict monthly household expenditures on groceries as a function of family size, household income, and household neighborhood (urban, suburban, and rural). The "neighborhood" variable in this model is ___. an independent variable - A market analyst is developing a regression model to predict monthly household expenditures on groceries as a function of family size, household income, and household neighborhood (urban, suburban, and rural). The "income" variable in this model is ____. an independent variable - A multiple regression analysis produced the following tables. For x 1 = 360 and x 2 = 220, the predicted value of y is ____________. 1314.70 - A multiple regression analysis produced the following tables.

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HOMEWORK 4 The regression equation for this analysis is ____________. y = 1959.71 - 0.46 x 1 - 2.16 x 2 - A multiple regression analysis produced the following tables. The sample size for this analysis is ____________. 18 - A real estate analyst has developed a multiple regression line, y = 60 + 0.068 x 1 – 2.5 x 2 , to predict y = the market price of a home (in \$1,000s), using independent variables, x 1 = the total number of square feet of living space, and x 2 = the age of the house in years. The regression coefficient of x 2 suggests this: _____ If the square feet area of living space is kept constant, a 1 year increase in the age of the homes will result in a predicted drop of \$2500 in the price of the homes
HOMEWORK 4 - A real estate analyst has developed a multiple regression line, y = 60 + 0.068 x 1 – 2.5 x 2 , to predict y = the market price of a home (in \$1,000s), using two independent variables, x 1 = the total

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