Below is the output results of the regression.
i) r=0.9878 implies that there is a strong relationship between expenditure and sales.
ii)expenditure =60000, is equivalent to 60 in (000)
the relationship between sales and expenditure is;
sales(00000)=3.871+0.125 expenditure(000)
=3.871+0.125(60)
=11.3817
For an expenditure of 60000, the sales associated to it is 1138170.
iii) 3-year moving average
the first point 3 year moving average is;
(5+5.6+5.8)/3=5.466667
the second point is;
(5.6+5.8+7.0)/3=6.133333
the third point is;
(5.8+7.0+7.2)/3=6.666667
the fourth point is;
(7.0+7.2+8.8)/3=7.666667
the fifth point is;
(7.2+8.8+9.2)/3=8.4
the sixth point is;
(8.8+9.2+9.5)/3= 9.166667
so the 3 point averages are
5.466667 , 6.133333 , 6.666667 , 7.666667 , 8.4 , 9.166667
iv) P(z<45)=0.31 and P(z>64)=0.08
the corresponding z values from the table is
"\\phi^{-1}(0.31)=-0.5"
"\\phi^{-1} (0.08)=1.41"
"z=\\frac{x-\\mu}{\\sigma}"
-0.5="\\frac{45-\\mu}{\\sigma}"
"-0.5\\sigma=45-\\mu"
"-0.5\\sigma+\\mu=45" .....(i)
"1.41=\\frac{64-\\mu}{\\sigma}"
"1.41\\sigma=64-\\mu"
"1.41\\sigma+\\mu=64" ...(ii)
solving equations (i) and (ii) simultaneously gives;
"\\sigma\\approx 10"
"\\mu \\approx 50"
The mean and standard deviation are 50 and 10 respectively.
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