An auto manufacturing company wanted to investigate how the price of one of its car models depreciates with age. The research department at the company took a sample of eight cars of this model and collected the following information on the ages (in years) and prices (in hundreds of dollars) of these cars.
Age
8
3
6
9
2
5
6
3
Price
45
210
100
33
267
134
109
235
1. Age, "X" is the independent variable
2. Price, "Y" the dependent variable
3.
"\\bar{Y}=\\dfrac{1}{n}\\sum _iY_i=\\dfrac{1133}{8}=141.625"
"SS_{XX}=\\sum_iX_i^2-\\dfrac{1}{n}(\\sum _iX_i)^2"
"=264-\\dfrac{(42)^2}{8}=43.5"
"SS_{YY}=\\sum_iY_i^2-\\dfrac{1}{n}(\\sum _iY_i)^2"
"=213565-\\dfrac{(1133)^2}{8}=53103.875"
"SS_{XY}=\\sum_iX_iY_i-\\dfrac{1}{n}(\\sum _iX_i)(\\sum _iY_i)"
"=4450\u2212\\dfrac{42(1133)}{8}=-1498.25"
"\\beta_1=\\dfrac{SS_{XY}}{SS_{XX}}=\\dfrac{-1498.25}{43.5}=-34.442529"
"\\beta_0=\\bar{Y}-\\beta_1\\cdot\\bar{X}=141.625+\\dfrac{1498.25}{43.5}(5.25)"
"=322.448276"
The regression equation is:
4.
The price of a 7-year-old car of this mode will be 81.35.
5.
A 18-year-old car of this mode does not exist.
"X\\leq9.36"
The price of a 9-year-old car of this mode will be 12.47.
A 10-year-old car of this mode does not exist.
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