Production Volume (units) | Total Cost ($) |
400 | 4000 |
450 | 5000 |
550 | 5400 |
600 | 5900 |
700 | 6400 |
750 | 7000 |
Production Target | Est. Cost ($) | |
500 |
Compute b1 and b0 (to 1 decimal).
b1
b0
Complete the estimated regression equation (to 1 decimal).
y = ... + x
According to this model, what is the change in cost (in dollars) for every unit produced (to 1 decimal)?
Compute the coefficient of determination (to 3 decimals). Note: report r2 between 0 and 1.
r2 =
What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)?
... %
The company's production schedule shows 500 units must be produced next month. What is the estimated total cost for this operation (to the nearest whole number)?
$ ...
Production X | Total Cost Y | X * Y | |||
400 | 4000 | 1600000 | 160000 | 16000000 | |
450 | 5000 | 2250000 | 202500 | 25000000 | |
550 | 5400 | 2970000 | 302500 | 29160000 | |
600 | 5900 | 3540000 | 360000 | 34810000 | |
700 | 6400 | 4480000 | 490000 | 40960000 | |
750 | 7000 | 5250000 | 562500 | 49000000 | |
Total | 3450 | 33700 | 20090000 | 2077500 | 1.95E+08 |
Equation of regression line is
b = 7.6
a =( 33700 - ( 7.6 * 3450 ) ) / 6
a = 1246.7
Equation of regression line becomes
b0 = 1246.7
b1 = 7.6
r = 0.979
Coefficient of Determination
Explained variation = 0.959* 100 = 95.9%
Unexplained variation = 1 - 0.959* 100 = 4.1%
When X = 500
= 1246.667
+ 7.6 X
= 1246.667
+ 7.6 * 500
= 5047
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