Exam 17: Time Series Forecasting and Index Numbers

In general, the number of dummy variables used to model constant seasonal variation is equal to the number of

Random shock is a value that is assumed to have been randomly selected that is the same for each and every time period.

Since a(n) ________ index employs the base-period quantities in all succeeding periods, it allows for ready comparisons for identical quantities of goods purchased between the base period and all succeeding periods.

Two forecasting models were used to predict the future values of a time series. The forecasts are shown below with the actual values. Which model is the most accurate? Why?

Weighting in exponential smoothing is accomplished by using ________.

The ________ component of a time series measures the fluctuations in a time series due to economic conditions of prosperity and recession with a duration of approximately 2 years or longer.

If a time series exhibits increasing seasonal variation, one approach is to first use a(n) ________ transformation that produces a transformed time series that exhibits constant seasonal variation. Then, ________ variables can be used to model the time series with constant seasonal variation.

The following data on prices and quantities for the years 1995 and 2000 are given for three products. Calculate the 2000 simple price index for each product separately.

A major drawback of the aggregate price index is that

Use the following price information for three grains. Calculate the Laspeyres index.

The forecaster who uses MSD (mean squared deviations) to measure the effectiveness of forecasting methods would prefer method 1, which results in several smaller forecast errors, to method 2, which results in one large forecast error equal to the sum of the absolute values of several small forecast errors given by method 1.

When the moving average method is used to estimate the seasonal factors with quarterly sales data, a(n) ________ period moving average is used.

Use the following price information for three grains. Calculate the aggregate price index.

The ________ test is a test for first-order positive autocorrelation.

Consider the following set of quarterly sales data given in thousands of dollars. Write an appropriate dummy variable model that incorporates a linear trend and constant seasonal variation.

XYZ Company, Annual Data Based on the information given in the table above, what is the average forecast error?

The linear regression trend model was applied to a time series of sales data based on the last 16 months of sales. The following partial computer output was obtained. Test the significance of the time term at α = .05. State the critical t value and make your decision using a two-sided alternative.

Consider the regression equation = 6.04 + .10 (t) and the data below. Compute the residual (error term) for period 8.

If the errors produced by a forecasting method for 3 observations are −1, −2, and −6, then what is the mean squared error or deviation?

The linear regression trend model was applied to a time series sales data set based on the last 24 months' sales. The following partial computer output was obtained. What is the predicted value of y when t = 25?