Principles of business forecasting / Keith Ord, Robert Fildes.

By:

Ord, Keith

Contributor(s):

Fildes, Robert

Material type:

TextPublication details: Mason : Cengage Learning, c2012.Description: xxii, 506 p. : ill. col. ; 26 cmISBN:

978113358440

Subject(s):

Business forecasting

DDC classification:

Contents:

1. Forecasting, the why and the how -- 2. Basic tools for forecasting -- 3. Forecasting trends: exponential smoothing -- 4. Seasonal series: forecasting and decomposition -- 5. State-space models for time series -- 6. Autoregressive Integrated Moving Average (ARIMA) models -- 7. Simple linear regression for forecasting -- 8. Multiple regression for time series -- 9. Model building -- 10. Advanced methods of forecasting -- 11. Judgment-based forecast -- 12. Putting forecasting methods to work -- 13. Forecasting in practice.

Summary: Forecasting techniques are shown in a variety of software platforms and the chapter organization provides an overview of forecasting in a variety of situations using time series and cross-sectional data. The focus then shifts to using extrapolative methods in forecasting, followed by statistical model-building. Finally, the authors cover more advanced techniques in the latter chapters, including the selection of the best forecasting method based on available data and the construction of a forecasting system with an organization.

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings
Item type	Current library	Call number	Status	Barcode
Books	Marbella International University Centre Library	338 ORD pri (Browse shelf(Opens below))	Available	10007

Includes bibliographical references and index.

1. Forecasting, the why and the how --
2. Basic tools for forecasting --
3. Forecasting trends: exponential smoothing --
4. Seasonal series: forecasting and decomposition --
5. State-space models for time series --
6. Autoregressive Integrated Moving Average (ARIMA) models --
7. Simple linear regression for forecasting --
8. Multiple regression for time series --
9. Model building --
10. Advanced methods of forecasting --
11. Judgment-based forecast --
12. Putting forecasting methods to work --
13. Forecasting in practice.

Forecasting techniques are shown in a variety of software platforms and the chapter organization provides an overview of forecasting in a variety of situations using time series and cross-sectional data. The focus then shifts to using extrapolative methods in forecasting, followed by statistical model-building. Finally, the authors cover more advanced techniques in the latter chapters, including the selection of the best forecasting method based on available data and the construction of a forecasting system with an organization.

There are no comments on this title.

to post a comment.

Click on an image to view it in the image viewer