Exam 16: Time Series Forecasting

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 -What is the predicted value of y when t = 17?

Dummy variables are used to model increasing seasonal variation.

A positive autocorrelation implies that negative error terms will be followed by _________ error terms.

Consider the quarterly production data (in thousands of units)for the XYZ manufacturing company below.The normalized (adjusted)seasonal factors are .9982,.9263,1.139,.9365 for winter,spring,summer,and fall,respectively.

Consider the quarterly production data (in thousands of units)for the XYZ manufacturing company below.The normalized (adjusted)seasonal factors are .9982,.9263,1.139,.9365 for winter,spring,summer,and fall,respectively.

Cyclical variation exists when the magnitude of the seasonal swing does not depend on the level of a time series.

$\text { XYZ Company - Annual data }$ Actual Demand Forecasted Demand 15 14 15 16 17 18 18 20 20 22 21 24 -Based on the information given in the table above,what is the MAPE?

$\text { XYZ Company - Annual data }$ Actual Demand Forecasted Demand 15 14 15 16 17 18 18 20 20 22 21 24 -Based on the information given in the table above,what is the MAD?

Use the following information for the three grains. Price 1990 Quantity Price 2000 Quantity Rice 30 2 35 1 Wheat 25 3 30 2 Oats 20 4 25 3 -Calculate the Laspeyres index.

$\text { XYZ Company - Annual data }$ Actual Demand Forecasted Demand 15 14 15 16 17 18 18 20 20 22 21 24 -Based on the information given in the table above,what is the MSD?

What is the predicted value of y when t = 20?

In the multiplicative decomposition method,the centered moving averages provide an estimate of:

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

The ________ component of time series refers to the erratic time-series movement that follows no recognizable or regular pattern.

Periodic patterns in a time series that complete themselves within a calendar year or less and then are repeated on a regular basis represent the __________ component of a time series.

The _______ component of time series reflects the long-run decline or growth in a time series.

Week Revenue Forecasted Revenue 1 200 225 2 240 220 3 300 285 4 270 290 5 230 250 6 260 240 7 210 250 8 275 240 -Compute the mean squared deviation (MSD).

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 S₀ for use in simple exponential smoothing.

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 4 period (quarter)centered moving average for the entire time series.

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 absolute deviation.