<u>Complete Question:</u>
The mean absolute error, mean squared error, and mean absolute percentage error are all methods to measure the accuracy of a forecast. These methods measure forecast accuracy by
a. adjusting the scale of the data.
b. determining how well a particular forecasting method is able to reproduce the time series data that are already available.
c. predicting the future values and wait for a pre-defined time period to examine how accurate the predictions were.
d. using the current value to estimate how well the model generates previous values correctly.
<u>Correct Option:</u>
These methods measure forecast accuracy by determining how well a particular forecasting method is able to reproduce the time series data that are already available.
<u>Option: B</u>
<u>Explanation:</u>
The forecast reliability is the level of proximity of the quantity assertion to the real or true value of that quantity in statistics. Typically, at the time the prediction is produced, the real value can not be calculated, as the assumption involves the future.
Accurate sales forecasting is an essential resource that businesses need to have. This helps managing directors gage desire for their goods. It allows companies handle inventories better. Sales forecasting enables businesses to look into the future and schedule their movements strategically to maximize development.
Answer:
hacer muchas cosas en el día como clases ejercicio comer tarea ayudar a limpiar la casa y más cosas en todo un día
True I think I am not 100% sure
Agricultural products is the answer
Answer:
3 boxes per day
Explanation:
Productivity refers to output per worker per period. Productivity can be measured per a group of workers or for the entire firm.
Productivity is expressed as follows=units produced/inputs used
for John and group: units produced =120 boxes
Inputs used 40 hours per day
Their productivity = 120/40 hrs
=3 boxes per day
