1(a) 1(b) 1(c)
Posted: Mon May 09, 2022 1:25 pm
1(a)
1(b)
1(c)
Which assumption of SRM is violated in the residual plot at the right? (a) The relationship is linear (b) The random errors are independent (c) The random errors have equal variance (d) The random errors are normally distributed.
The heights (y) of 50 men and their shoes sizes (x) were obtained. The variable height is measured in centimeters and the shoe sizes of these 50 men ranged from 8 to 11. From these 50 pairs of observations, the least squares regression line predicting height from shoe size was computed to be û = 130.455 + 4.7498x. What height would you predict for a man with a shoe size of 13? (a) 130.46cm (b) 192.20cm (c) 182.70cm (d) I would not use this regression line to predict the height of a man with a shoe size of 13.
The scatter plot of sales (y) of half-gallon orange juice versus the price (x) is given below. We apply log transform on both y and x to fit the nonlinear pattern. 150 125 100 Sales 75 50 25 . ii O 1 1.5 2 2.5 3 3.5 4 4.5 Price
Transformed Fit Log to Log log(yi) = 4.81 – 1.75 x log(xi) Summary of Fit RSquare 0.755 Adjusted RSquare 0.750 Root Mean Square Error 0.386 Mean of Response 3.136 Observations (or Sum Wgts) 50 Parameter Estimates Term Estimate Std Error t Ratio Prob>|t| Intercept 4.8 0.148 32.50 <.0001* Log(Price) -1.75 0.144 -12.17 <.0001* Assume the transformed x and y agrees with SRM, which of the following statement is correct? (a) As the price increase by 1%, the sales decrease by 1.75% on the average (b) As the price increase by $1, the sales decrease by 1.75 units on the average. (c) As the price increase by 1%, the sales decrease by 1.75 units (d) As the price increase by 1$, the sales decrease by 175%.
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The heights (y) of 50 men and their shoes sizes (x) were obtained. The variable height is measured in centimeters and the shoe sizes of these 50 men ranged from 8 to 11. From these 50 pairs of observations, the least squares regression line predicting height from shoe size was computed to be û = 130.455 + 4.7498x. What height would you predict for a man with a shoe size of 13? (a) 130.46cm (b) 192.20cm (c) 182.70cm (d) I would not use this regression line to predict the height of a man with a shoe size of 13.
The scatter plot of sales (y) of half-gallon orange juice versus the price (x) is given below. We apply log transform on both y and x to fit the nonlinear pattern. 150 125 100 Sales 75 50 25 . ii O 1 1.5 2 2.5 3 3.5 4 4.5 Price
Transformed Fit Log to Log log(yi) = 4.81 – 1.75 x log(xi) Summary of Fit RSquare 0.755 Adjusted RSquare 0.750 Root Mean Square Error 0.386 Mean of Response 3.136 Observations (or Sum Wgts) 50 Parameter Estimates Term Estimate Std Error t Ratio Prob>|t| Intercept 4.8 0.148 32.50 <.0001* Log(Price) -1.75 0.144 -12.17 <.0001* Assume the transformed x and y agrees with SRM, which of the following statement is correct? (a) As the price increase by 1%, the sales decrease by 1.75% on the average (b) As the price increase by $1, the sales decrease by 1.75 units on the average. (c) As the price increase by 1%, the sales decrease by 1.75 units (d) As the price increase by 1$, the sales decrease by 175%.