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A company uses regression analysis to establish a total cost equation for budgeting purposes.
Data for the past four months is as follows:
Month Total cost Quantity produced
$’000 $’000
1 57.5 1.25
2 37.5 1.00
3 45.0 1.50
4 60.0 2.00
200.0 5.75
The gradient of the regression line is 17.14.
What is the value of a?
A 25.36
B 48.56
C 74.64
D 101.45sir,here why dont we directly use y=a+bx to find the value of a..
we have total cost Y=200, b=17.14, x=5.75Apart from the fact that you need to divide the totals by 4 (to get the average) rather than use the totals themselves, that is exactly what you would be doing if you used the formula for a on the formula sheet!!
If you used the totals instead of the averages you would get a = 101.45 which would obviously be wrong anyway (just try a = 101.45 for any of the months and it would give ridiculous answers).
If the regression equation (in $000) linking sales(Y) to advertising expenditure (X) is given by Y = 4000 + 12x , what is the forecast sales when $150,000 is spent on advertising,to the nearest $ ?
The answer given is $5,800,000. Could you please explain me how that answer arrived?
The equation is given in $000.
So you use x = 150 in the formula, which gives y = 5,800.
This is the sales in thousands, so the forecast is 5,800 x 1,000 = 5,800,000
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