Copyright © 2012 Pearson Education, Inc. All rights reserved. Chapter 10 Introduction to Time Series Modeling and Forecasting.

Copyright © 2012 Pearson Education, Inc. All rights reserved.

Chapter 10

Introduction to Time Series Modeling and Forecasting


Section 10.1

What Is a Time Series


Section 10.2

Time Series Components

Copyright © 2012 Pearson Education, Inc. All rights reserved.10- 4

Figure 10.1 The components of a time series


Section 10.3

Forecasting Using Smoothing Techniques



Figure 10.2 MINITAB plot of quarterly power loads



Figure 10.3 MINITAB plot of quarterly power loads and 4-point moving average



Figure 10.4 MINITAB printout of exponentially smoothed quarterly power loads


Figure 10.5 MINITAB plot of exponentially smoothed quarterly power loads







Section 10.4

Forecasting: The Regression Approach



Figure 10.6 SAS scatterplot of sales data


Figure 10.7 SAS printout for straight-line model of yearly sales revenue

continued on next slide


Figure 10.7 SAS printout for straight-line model of yearly sales revenue (cont’d)


Figure 10.8 SAS printout for quarterly power load model



Figure 10.8 SAS printout for quarterly power load model (cont’d)


Section 10.5

Autocorrelation and Autoregressive

Error Models


Figure 10.9a Autocorrelation functions for several first-order auto regressive error models: Rt = 1Rt-1 + t


Figure 10.9b Autocorrelation functions for several first-order auto regressive error models: Rt = 1Rt-1 + t


Figure 10.9c Autocorrelation functions for several first-order auto regressive error models: Rt = 1Rt-1 + t


Section 10.6

Other Models for Autocorrelated Errors

(Optional)


Figure 10.10 Autocorrelations for a first-order moving average model: Rt = t + t-1


Figure 10.11 Autocorrelations for a fourth-order moving average model


Section 10.7

Constructing Time Series Models


Figure 10.12 A seasonal time series model


Figure 10.13 Seasonal model for quarterly data using dummy variables


Section 10.8

Fitting Time Series Models with Autoregressive Errors


Figure 10.14 SAS printout for model of annual sales revenue


Figure 10.15 MINITAB residual plot annual sales model


Figure 10.16 SAS printout for annual sales model with autoregressive errors



Figure 10.16 SAS printout for annual sales model with autoregressive errors (cont’d)



Section 10.9

Forecasting with Time Series Autoregressive Models



Figure 10.17 SAS printout of forecasts of annual sales revenue using straight-line model with autoregressive errors



Section 10.10

Seasonal Time Series Models: An Example


Figure 10.18 Water usage time series


Figure 10.19 SAS printout for time series model of water usage


Figure 10.20 Forecasts of water usage


Section 10.11

Forecasting Using Lagged Values of the Dependent Variable (Optional)

Copyright © 2012 Pearson Education, Inc. All rights reserved. Chapter 10 Introduction to Time Series Modeling and Forecasting.

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