0 to Infinity
"MAPE is commonly used in quantitative forecasting methods because it produces a measure of relative overall fit. The absolute values of all the percentage errors are summed up and the average is computed." (according to John Galt University)
3.000 as a percentage = 300.0% while if you mean 3,000; 3,000 as a percentage = 300,000%
Assuming you mean as a percentage of 1, 0.59 is equal to 59 percent.
Did you mean 41/100 as a percentage? If so it is 41%, because a percentage is a number out of 100!I would like of how I got the 41/ 100 percentage
No it is not true. The absolute value of a number is simply the value of the number with a positive sign.
The mean absolute percent prediction error (MAPE), .The summation ignores observations where yt = 0.
"MAPE is commonly used in quantitative forecasting methods because it produces a measure of relative overall fit. The absolute values of all the percentage errors are summed up and the average is computed." (according to John Galt University)
The lower the better
It is the mean absolute deviation.
An absolute mean is a mean of the absolute magnitude of a function with both positive and negative values.
The error, which can be measured in a number of different ways. Error, percentage error, mean absolute deviation, standardised error, standard deviation, variance are some measures that can be used.
The difference between the corrected reading and the mean (average) reading is called 'Absolute error.
It means that, relative to the true value of whatever you are trying to measure, the estimated (or calculated) value is quite a long way off.If the real value of something is 5 but is measure as 7 the absolute error is 7 - 5 = 2, but the percentage error is 100*2/5 = 40%If the true value is 100 and it is measured as 103, the absolute error is 103 - 100 = 3 which is greater than before. But the percentage error is only 100*3/100 = 3%.
= absolute error/ mean value of measured quantity times 100 50/5 times 100= 1000%
high percent error is the absolute value of something that is multiplied
The Mean Absolute Deviation indicates how clustered (close together) the data is, i also indicates the average of the distance of the values and the mean.
You can compare forecasting methods by one of these methods: 1- MAD(mean absolute deviation) 2-MSE (mean square error) 3-MAPE(mean absolute percentage error) Notes: 1-MAD is the preferred method since it does not require squaring the errors and this is the only difference between MAD and MSE . 2-If you want to relate the error relative to the actual demand use MAPE that is because in MAPE you will divide the error by the actual demand.