Question

3. World truck production (fictional) ON HTAM Year x 1984 1985 1986 1987 1988 15.9 16.3 16.8 17.2 17.5 Trucks y (millions) a)
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Answer #1

a)

Trucks(millions) vs Year 17.5 17.0 у 16.5 16.0 1984 1985 1986 1987 1988 х

b)

Note that, r^2 =\frac{\sum (x_i-\bar x)(y_i-\bar y)}{\sqrt{\sum (x_i-\bar x)^2 \sum (y_i-\bar y)^2}}

Serial no. C y_i (x_i-\bar x)^2 (y_i-\bar y)^2 (x_i-\bar x)(y_i-\bar y)
1 1984 15.9 4 0.7056 1.68
2 1985 16.3 1 0.1936 0.44
3 1986 16.8 0 0.0036 0
4 1987 17.2 1 0.2116 0.46
5 1988 17.5 4 0.5776 1.52
Total 9930 83.7 10 1.692 4.1
mean 1986 16.74

From the table of calculations above we have

r^2 =\frac{4.1}{\sqrt{10*1.692}}=0.9967 \Rightarrow r = 0.9983

c) The equation of the least square regression is : Y= a+bX

where the least square estimates are as follows, \hat b=\frac{\sum(x_i-\bar x)(y_i-\bar y)}{\sum(x_i-\bar x)^2}=\frac{4.1}{10}=0.41

\hat a=\bar y - \hat b\bar x = 16.74 - (0.41)*1986=-797.52

Hence ,

Y = -797.52 + 0.41 X is the required equation.

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