Exam 16: Time Series Forecasting

A time series obtained from quarterly data exhibits an increasing linear trend and constant seasonal variation.The most appropriate way to model this time series would be to use

While a simple index is calculated by using the values of one time series,an aggregate index is computed based on the accumulated values of more than one time series.

The ________ index is a weighted aggregate price index that requires quantity data for each year.

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: Variable Estimate T Prob. Intercept 18.100 4.45 .001 Time 3.2456 7.71 .000 -Test the significance of the time term at ? = .05.State the critical t value and make your decision using a two-sided alternative.

When using simple exponential smoothing,the more recent the time series observation,the _________ its corresponding weight.

Week Revenue Forecasted Revenue 1 120 125 2 130 125 3 110 125 4 140 125 5 110 125 6 130 125 -Compute the mean squared deviation (MSD).

Consider the prediction equation $\hat { y }$ = 6.04 + 0.10(t)and the data below. Time period Sales (y) 1 6.1 2 6.0 3 6.1 4 6.3 5 6.8 6 6.8 7 7.0 8 7.1 9 7.0 10 7.1 11 6.8 12 7.0 13 7.2 14 7.4 15 7.5 -Compute the predicted value of sales for period 7 and 8.

When computing moving averages for quarterly sales data,a ______ period moving average is used.

Listed below is the price of a pair of men's boots over a 50 year time period. Year Price 1950 \ 22.45 1960 \ 32.33 1970 \ 44.90 1980 \ 69.75 1990 \ 80.05 2000 \ 87.28 Find the simple index numbers for the data with 1950 as the base year.

The multiplicative decomposition method should not be used to forecast for a time series with increasing seasonal variation.

Week Revenue Forecasted Revenue 1 120 125 2 130 125 3 110 125 4 140 125 5 110 125 6 130 125 -Compute the total forecast error (sum of the forecast error terms).

The ________ index is a weighted aggregate price index that uses the base period quantities as weights in all succeeding time periods.

Consider the following data: Time Demand 1 17 2 21 3 19 4 23 5 18 6 16 7 20 8 18 9 22 10 20 11 15 12 22 -Calculate S₅ using simple exponential smoothing if S₃ = 19.064 and a = 0.2.

Assume that the current date is February 1, 2013. The linear regression model was applied to a monthly time series data based on the last 24 months' sales. (from January 2011 through December 2012). The following partial computer output summarizes the results. Coeffficient Estimate t Intercept 4.3 2.07 Slope 1.6 2.98 -The actual sales for February 2013 were 43.7.What is the forecast error for February 2013?

If the errors produced by a forecasting method for 3 observations are +3,+3 and -3,then what is the mean squared deviation (MSD)?

The recurring up-and-down movement of a time series around trend levels that last more than one calendar year is called _____.

The following data on prices and quantities for the years 1995 and 2000 are given for three products. Product 1995 Price Quantity Product 2000 Price Quantity \ 4 10 \ 8 15 \ 8 15 \ 6 10 \ 3 8 \ 4 12 -Calculate the Laspeyres index.

Consider the quarterly production data (in thousands of units)for the XYZ manufacturing company below. Year Quarter 1998 1999 2000 Winter 9 21 25 Spring 16 20 27 Summer 16 30 34 Fall 17 23 32 -Calculate the average seasonal factor for each quarter

State the two-sided null and alternative hypothesis to test the significance of the t² term.

In the Durbin-Watson test,if the calculated d-statistic is greater than the upper value of the d-statistic,then: