Fill in the blanks.

Choose the answers here from questions 1-10.

Forecast

Cyclical pattern

Moving averages method

Time series

Forecast error

Exponential smoothing

Stationary time series

Mean absolute error

Smoothing constant

Trend

Mean squared error

Seasonal pattern

Mean absolute percentage error

1.

A parameter of the exponential smoothing model that provides the weight given to the most recent time series value in the calculation of the forecast value.

2.

A forecasting technique that uses a weighted average of past time series values as the forecast.

3.

A method of time series forecasting that uses the average of the most recent n data values as the next forecast value.

4.

It measures the accuracy of the forecast using the average of absolute values of the errors as a percentage of the corresponding forecast values.

5.

A prediction of future values of a time series.

6.

Gathered information from different periods as a set of observations for variability measurements.

7.

A time-series whose statistical properties are independent of time.

8.

The long-run shift or movement in the time series, observable over several periods of time.

9.

The component of the time series that show a periodic pattern over one year or less.

10.

The average value of forecast errors.

11.

Consider the following time series data:

Month	1	2	3	4	5	6	7	8	9
Value	24	13	20	12	19	23	15	?	?

What type of pattern exists in the data?

Group of answer choices

Seasonal

Horizontal

Cyclical

Trend

12.

Consider the following time series data:

Month	1	2	3	4	5	6	7	8	9
Value	24	13	20	12	19	23	15	?	?

Develop a three-week moving average for this time series.

____ What is your 8th-month value?

____ What is your 9th-month value?

____ Compute for MSE for 8th month.

____ Use smoothing constant of .20 to compute the 8th-month value. (2 decimal places only)

____ Use smoothing constant of .20 to compute the 9th-month value.

13.

Consider the following data series:

Month	1	2	3	4	5	6	7	8	9
Value	24	13	20	12	19	23	15	?	?

Identify if your forecast values are Accurate, Overestimated, Underestimated. Use A for accurate, O for overestimated and U for underestimated.

____ Week 3

____ Week 4

____ Week 5

____ Week 6

____ Week 7