An auctioneer of antique Iranian rugs kept records of his weekly auctions in order to determine the relationships among price, age of carpet or rug, number of people attending the auction, and the number of times the winning bidder had previously attended his auctions. He felt that, with this information, he could plan his auctions better, serve his steady customers better, and make a higher overall profit for himself. The results shown in the accompanying table were obtained.
Extracted text: A). Write down the equation of the sample regression line and carefully interpret the meaning of the coefficients. B). At 5% level of significance, is there sufficient evidence of a linear relationship between price and age? You must show all necessary work for your analysis to be statistically valid. C). At 5% level of significance, is there sufficient evidence of a linear relationship between price and audience size? You must show all necessary work for your analysis to be statistically valid. D). At 5% level of significance, is there sufficient evidence of a linear relationship between price and previous attendance? You must show all necessary work for your analysis to be statistically valid. E). At 5% level of significance, is there sufficient evidence to conclude that the linear model is useful? You must show all necessary work for your analysis to be statistically valid. F). Assess the linear model and explain carefully the procedures used in the assessment. G). Carefully explain the concept of collinearity. Is there evidence of noticeable collinearity as far as the statistical analysis you have performed in this problem? Explain carefully. What is your recommendation about previous attendance as a variable in the linear model and whether or not it contributes information for the prediction of price? Explain carefully. H). Examine the residual plots. Carefully explain what information each plot provides in terms of the above study?
Extracted text: An auctioneer of antique Iranian rugs kept records of his weekly auctions in order to determine the relationships among price, age of carpet or rug, number of people attending the auction, and the number of times the winning bidder had previously attended his auctions. He felt that, with this information, he could plan his auctions better, serve his steady customers better, and make a higher overall profit for himself. The results shown in the accompanying table were obtained. Price (Dollars) Age 1,080 2,540 1,490 960 Audience Size Previous Attendance 80 40 1 150 80 12 85 55 3 55 45 2,100 1,820 2,230 1,490 1,620 1,260 1,880 2,080 2,150 1,940 1,860 2,240 2,950 2,370 1,240 1,620 2,120 1,090 1,850 2,220 1,420 2,140 140 70 95 65 5 140 80 7 80 60 9 90 65 10 55 70 60 8. 90 7 100 100 5 120 85 3 95 80 90 80 6. 135 90 175 120 10 150 115 10 55 55 3 70 75 5 120 100 50 50 65 65 9. 125 95 7 60 45 8 115 95