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Chapter 18 provides knowledge of time series. When you finish this chapter, you should be able to: Define the four components of a time series, determine a linear trend equation, compute a moving average, compute the trend equation for a nonlinear trend,. | Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. TIME Series Chapter 18 Define the four components of a time series 1. Determine a linear trend equation 2. Compute a moving average 3. Compute the trend equation for a nonlinear trend 4. Use trend equations to forecast future time periods and to develop seasonally adjusted forecasts 5. Determine and interpret a set of seasonal indexes 6. Deseasonalize data using a seasonal index 8. When you have completed this chapter, you will be able to: Identify cyclical fluctuations 7. Compute and evaluate forecasts 9. TIME Series is a collection of data recorded over a period of time ( data may be recorded weekly, monthly, or quarterly) Components Secular Trend Cyclical Variation Seasonal Variation is the long run direction of the Time Series is the fluctuation above and below the trend line is the pattern in a time series; these patterns tend to repeat themselves from year to year .and Episodic variations are . | Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. TIME Series Chapter 18 Define the four components of a time series 1. Determine a linear trend equation 2. Compute a moving average 3. Compute the trend equation for a nonlinear trend 4. Use trend equations to forecast future time periods and to develop seasonally adjusted forecasts 5. Determine and interpret a set of seasonal indexes 6. Deseasonalize data using a seasonal index 8. When you have completed this chapter, you will be able to: Identify cyclical fluctuations 7. Compute and evaluate forecasts 9. TIME Series is a collection of data recorded over a period of time ( data may be recorded weekly, monthly, or quarterly) Components Secular Trend Cyclical Variation Seasonal Variation is the long run direction of the Time Series is the fluctuation above and below the trend line is the pattern in a time series; these patterns tend to repeat themselves from year to year .and Episodic variations are unpredictable, but can usually be identified, such as a flood or hurricane Residual variations are random in nature and cannot be identified Irregular Variation is divided into two components: TIME Series Components Continued Examples. Text Chart 18-1 Excel Secular Trend Secular Trend almost constant Text Chart 18-2 Excel Text Chart 18-3 Excel Secular Trend Increasing Trend Text Chart 18-4 Excel Secular Trend Declining Trend Text Chart 18-5 Excel Cyclical Variation Figure 18-6 Text Chart 18-6 Excel Seasonal Variation Linear Trend The long term trend equation (linear) Estimated by the least squares equation for time t is: TIME Series Example. a bt b ty y t t t a y n b t n ( )( ) ( ) = + = - - = - æ è ç ö ø ÷ nS S S nS S S S 2 2 y Continued TIME Series The owner of Farley Homes would like a forecast for the next couple of years of new homes that will be constructed in the Edmonton area. Listed below are the sales of new homes constructed in the area for the last 5 years. .
