Time Series Analysis & Forecastting

Question 1

(T/F) Time series methods base forecasts only on past values of the variables

Answer 1

True

Question 2

(T/F) All quarterly time series contain seasonality

Answer 2

False

Question 3

(T/F) A four-period moving average forecast for period 10 would be found by averaging the values from periods 10, 9, 8, and 7

Answer 3

False

Question 4

(T/F) Smoothing methods are more appropriate for a stable time series than when significant trends or seasonal patterns are present

Answer 4

True

Question 5

(T/F) The exponential smoothing forecast for any period is a weighted average of all the previous actual values for the time series

Answer 5

True

Question 6

(T/F) An alpha value of 0.2 will cause an exponential smoothing forecast to react more quickly to a sudden drop in demand than will and alpha value of 0.4

Answer 6

False

Question 7

(T/F) Time series data can exhibit seasonal patterns of less than one month duration

Answer 7

True

Question 8

All of the following are true about time series methods except:
A) they discover a pattern in historical data and project it into the future
B) They involve the use of expert judgment to develop forecasts
C) they assume that the pattern of the past will continue into the future
D) their forecasts are based solely on past values of the variable of past forecast errors

Answer 8

B

Question 9

Season patterns…
A) cannot be predicted
B) are regular repeated patterns
C) are multiyear runs of observations above or below the trend line
D) reflect a shift in the time series over time

Answer 9

B

Question 10

Forecast errors…
A) are the difference in successive values of a time series
B) are the differences between actual and forecast values
C) should all be non-negative
D) should be summed to judge the goodness of a forecasting model

Answer 10

B