Answer:
$2,700
Explanation:
Calculation for what should this professor be willing to pay in rent per month
First step is to calculate the Transportation cost per week
Transportation cost = ($25*4 hrs)* 3 per week
Transportation cost =$100*3 per week
Transportation cost= 300 a week
Now let calculate the rent per month
Rent per month= $1500 + ($300*4)
Rent per month=$1,500+$1,200
Rent per month= $2,700
Therefore what should this professor be willing to pay in rent per month to live near campus if her hourly wage rate is $25 will be $2,700
Answer
The answer and procedures of the exercise are attached in the following archives.
Step-by-step explanation:
You will find the procedures, formulas or necessary explanations in the archive attached below. If you have any question ask and I will aclare your doubts kindly.
Answer:
Cheap Florida Auto Insurance. Low Rates from $53.99 / Month!
Explanation:
When both parties are expecting to gain from a transaction, they are conducting a Voluntary trade. In a Voluntary trade, both the sell and buyers involved in the transaction based on their own free will and expecting to gain a profit from the trade
Answer:
Answer is the one which produces values which compare well with actual values based on a standard measure of error.
Explanation:
Exponential smoothing is one means of preparing short-term sales forecasts on a routine basis. To use exponential smoothing, however, one must decide the proper values for the smoothing constants in the forecasting model. One method for selecting the smoothing constants involves conducting a grid search to evaluate a wide range of possible values.
Exponential smoothing forecasting methods use constants that assign weights to current demand and previous forecasts to arrive at new forecasts. Their values influence the responsiveness of forecasts to actual demand and hence influence forecast error. Considerable effort has focused on finding the appropriate values to use.
One approach is to use smoothing constants that minimize some function of forecast error. Thus, in order to select the right constants for forecasting, different values are tried out on past time series, and the ones that minimize an error function like Mean Absolute Deviation (MAD) or Mean Squared Error (MSE) are the ones used for forecasting
