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:
Answer:
53,337
Step-by-step explanation:
Answer:
12(j+t) + 15 = c
Step-by-step explanation:
So, lets go over what we know.
First off, for simplicity, lets consider Johnathan as J, and Trina as T.
We know that both J and T produce 12 dollars each per hour.
We know that J gets a extra 15 dollars.
We can think of the amount they produce each hour as the time they work in total, times the money they make a hour, which is 12.
We can think of this first part where the total time they work is (J + T)
The 12 dollars they get an hour can be though of as multiplying this sum: 12(J+T)
Finally, we know that J gets an extra 15 dollars.
This is not dependent on time, like the other variables, so we simply add it to the sum of what they make in the end:
12(J+T)+15
This looks like answer C.
Answer:
C
Hope this helps!
Answer:
midpoint P(6, 4)
Step-by-step explanation:
As we can see here any negative number subtracting another negative number leads to adding. So we would have -6+2 which would be -4. So therefore your answer is -4
