WILL GIVE 100 POINTS TO WHOEVER ANSWER THIS CORRECTLY. In the similarity transformation of abc to def, abc was dilated by a scal
e factor of ?, reflected across the , and moved through the translation
1 answer:
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Answer:
d. The mean absolute percentage error (MAPE) does not depend on the units of the forecast variable.
Step-by-step explanation:
A forecast error is the difference between the actual or real and the predicted or forecast value of a time series or any other phenomenon of interest. Here “error” does not mean a mistake, it means the unpredictable part of an observation.
There are many different ways to summarize forecast errors in order to provide meaningful information.
Scale-dependent errors. The forecast errors are on the same scale as the data. The two most commonly used scale-dependent measures are based on the absolute errors or squared errors:
Percentage errors. Percentage errors have the advantage of being unit-free, and so are frequently used to compare forecast performances between data sets. The most commonly used measure is:
For this type of problem,
It is stated that the weight of steel is 32.6 lbs per foot
Meaning, every foot of steel beam weighs 32.6.
So 2 feet of steel beam would weigh 32.6 x 2 = 65.2 lbs
and 3 feet will be 32.6 x 3 = 97.8 lbs
Since we have a limit of 5000 lbs which is the capacity of the truck.
We can have an equation :
Where x is the number of foot
Solve the value of x by dividing both sides by 32.6 :
So the answer is 153.37 feet of steel beam