An appraiser collected the data found in file dat9-18.xlsx that accompanies this book describing the auction selling price, diameter (in inches), and item type of several pieces of early 20th century metal tableware manufactured by a famous artisan. the item type variable is coded as follows: b bowl, c casserole pan, d = dish, t = tray, and p = plate. the appraiser wants to build a multiple regression model for this data to predict average selling prices of similar items. a. construct a multiple regression model for this problem. what is the estimated regression function? b. interpret the value of the r2 statistic for this model. c. construct an approximate 95% prediction interval for the expected selling price of an 18-inch diameter casserole pan. interpret this interval. d. what other variables not included in the model might explain the remaining variation in auction selling prices for these items?

Net income and owner's equity for four businesses four different proprietorships, jupiter, mars, saturn, and venus, show the same balance sheet data at the beginning and end of a year. these data, exclusive of the amount of owner's equity, are summarized as follows: total assets total liabilities beginning of the year $550,000 $215,000 end of the year 844,000 320,000 on the basis of the preceding data and the following additional information for the year, determine the net income (or loss) of each company for the year. (hint: first determine the amount of increase or decrease in owner's equity during the year.) jupiter: the owner had made no additional investments in the business and had made no withdrawals from the business. mars: the owner had made no additional investments in the business but had withdrawn $36,000. saturn: the owner had made an additional investment of $60,000 but had made no withdrawals. venus: the owner had made an additional investment of $60,000 and had withdrawn $36,000. jupiter net income $ mars net income $ saturn net income $ venus net income $

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