The number of times per year a person uses rapid transit is a linear function of income: Y= 1.2+2.4X1+8.4X2+15.6X3, where X1,X2,X3 are dummy variables for medium, high, and very high incomes, respectively (the low-income category has been omitted). What is the predicted number of annual trasnit trips per year for each of the four income categories? O Low:1.2, Medium: 2.4, High: 8.4, Very High: 15.6 O Low:1.2, Medium: 3.6, High: 9.6, Very High: 16.8 O Low:0, Medium: 1.2,, High: 3.8, Very High: 8.6 O Low:1.2, Medium: 3.6, High: 12, Very High: 27.6

A collector of antique clocks sold at auction believes that the price received for the clocks may be modeled as a linear function of the age of the clocks and the number of bidders at the auction. After a preliminary study and collection of 32 observations, the collector came up with the following second-order model: y = BO+B₁x₁+B₂x₂ + ß3 x1x2 +B4x² +ɛ, where y: price of a clock; x₁: age of a clock; x2: the number of bidders. Considering the output below and by setting a = 0.05, answer the following questions. The regression equation is Price = 262 +2.26 Age + 14.2 Bidder + 1.13 AgeBid 4.20 Bid^2 Predictor Constant -261.7 2.260 14.21 Age Bidder AgeBid Bid^2 S = 84.512 Coef SE Coef 1.1301 -4.196 Analysis of Variance Source 404.4 2.052 R-Sq= 96.0% Variable Age Bidder AgeBid Bid^2 60.83 0.23 5.17 0.000 0.219 1.344 -3.12 0.004 R-Sq (adj) DF Regression 4 4606950 Residual Error 27 192840 Total 31 4799790 SS T P -0.65 0.523 1.10 0.280 0.817 a. Is the model useful as a whole? Apply an…

Suppose that the number of tee shirts sold (N) depends linearly on the price charged (x). Write an equation showing this dependence.