Question

1. Create a prediction for period 7 using the naive model.

2. Create your forecast using the naive model. Calculate all the errors for each period. What is the error for period 3?

3. What is the mean sqaured error?

4. Find the root mean squared error

Answer 1

solution:

  

Consider data

Month	1	2	3	4	5	6
Values	24	13	21	13	20	24

--> Calculating errors using Most Recent Value (Naive method) Method

Naive Forecasting: Naive forecasting is a forecasting Technique which uses quantitative data for its data estimation.It is easy to  forecast the next month data by simply putting the previous data of last month to next month.

Using naive method forecast for next month is;

Month	Value (A)	Forecast Naive Method (N)	Error (A-N)	Absolute Error | (A-N) |	Squared Absolute Error |(A-N) |^2	|%Error|
1	24
2	13	24	-11	11	121	84.62%
3	21	13	8	8	64	38.10%
4	13	21	-8	8	64	61.54%
5	20	13	7	7	49	35%
6	24	20	4	4	16	16.67%
7		24		= 38	=314	=235.93%

1) Forecast for month 7 = 24

2) Error for period 3 is - 8

i) Mean Absolute Deviation

MAD = Absolute error / No.of months forecasted

= 38 / 5

= 7.6

ii)Mean Squared Error (MSE) is Squared Absolute Error divided by No.of months forecasted

MSE = |(A-N) |^2 / 5

= 314 / 5

= 62.8

iii) Mean Absolute Percentage Error

MAPE = |%Error| / No.of months forecasted

= 235.93% / 5

= 47.186%

3) MSE = 62.8

4) Root Mean Squared Error = = 7.925