Exam 18: Models for Time Series and Forecasting

Time periods The following are the values of a time series for the first four time periods: 1 2 3 4 23 25 28 24 -Using exponential smoothing,with $\alpha$ = 0.30,what is the forecasted value for time period 5?

Which of the following will not be present in a de-seasonalized time series?

One of the assumptions required by the regression model is that the residuals (errors)be independent of each other.When this assumption is not met:

The Durbin-Watson test can be used to determine whether the residuals in a regression model are independent.

In determining weekly seasonal indexes for gas consumption,the sum of the 52 means for gas consumption as a percentage of the moving average is 5050.To get the seasonal indexes,each weekly mean is to be multiplied by:

Which of the four time series components is more likely to exhibit the steady growth of the population of the United States from 1950 to 2000?

The results of a quadratic model fit to time series data were $\hat{y}$ = 7.5 - 0.25t + 3.5t2, where t = 1 for 1995. The forecasted value for 2002 is:

Time periods The following are the values of a time series for the first four time periods: 1 2 3 4 23 25 28 24 -Using a four-period moving average,what is the forecasted value for time period 5?

What is an index number?

Overtime The quarterly overtime hours (in 1000s)recorded in a large steel mill are shown below. Year Quarter Overtime Hours 1995 1 32 2 15 3 21 4 28 1996 1 35 2 16 3 27 4 29 1997 1 36 2 21 3 25 4 37 1998 1 41 2 29 3 31 4 40 Using the regression technique,the linear trend line $\hat{y}$ = 21.675 + .854t was computed. -What do the seasonal indexes tell us?

Identify the following equation: $\mathrm { E } _ { \mathrm { t } } = \alpha \cdot \mathrm { y } _ { \mathrm { t } } + ( 1 - \alpha ) \cdot \mathrm { E } _ { \mathrm { t } - 1 }$ .

When data are a sequence of observations over regular intervals of time,they are referred to as a ____________________.

Overtime The quarterly overtime hours (in 1000s)recorded in a large steel mill are shown below. Year Quarter Overtime Hours 1995 1 32 2 15 3 21 4 28 1996 1 35 2 16 3 27 4 29 1997 1 36 2 21 3 25 4 37 1998 1 41 2 29 3 31 4 40 Using the regression technique,the linear trend line $\hat{y}$ = 21.675 + .854t was computed. -Calculate the seasonal indexes based on the regression trend line.

In autoregressive forecasting,each independent variable represents the value of the dependent variable for a previous time period.

When exponential smoothing is used in fitting a curve to a time series,the approach is slightly different from its application to forecasting.Compare the appropriate formulas and point out how they differ.

When exponential smoothing is used for forecasting,the forecast will tend to be too high for time series that are increasing (positive trend)and too low for time series that are decreasing (negative trend).

The classical time series model combines the various components in which of the following ways?

An auto parts supplier forecasted 1998 annual sales of $800,000.Seasonal indexes of sales for each quarter of the year were: I - 80,II - 112,III - 117,IV - 91.The sales forecast for quarter II was:

Selecting a large the number of periods (N)for a centered moving average

If a company's inventory costs were $3.5 million in 1995 (base period)and $5.95 million in 2002,what is the index number for 2002? What does it mean?