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Introduction to Time-series Modeling and Forecasting in Business and Economics

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  • 625 stron
  • 22 godziny czytania

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This text is designed for forecasting courses in economics, management science and decision science departments, and emphasizing understanding and application rather than the theoretical and computational aspects of the statistical techniques used. Chapter 2 on describing and transforming data and chapter 9 on single equation econometric modelling offer in-depth discussions of topics fundamental to time-series analysis that most other texts cover in a cursory fashion. Appropriate to students with a minimal mathematics background (basic statistics and algebra), the text contains a review section on statistics and multiple regression and can be used effectively at both the graduate and undergraduate levels. The book's readibility is complemented by its inclusion of numerous visual aids such as graphs, tables and fully-worked examples. An ongoing case based on actual company data illustrates the use of important procedures described in each chapter. There is also in-depth coverage of popular computer software packages (for example, Lotus, MicroTSP, Minitab) including written programs and outputs. Two chapters on the Box-Jenkins procedure provide straightforward, intuitive, understandable coverage of a topic that is often difficult for students to grasp.

Zakup książki

Introduction to Time-series Modeling and Forecasting in Business and Economics, Patricia E. Gaynor, Rickey C. Kirkpatrick

Język
Rok wydania
1994
Oprawa
(twarda)
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Tytuł
Introduction to Time-series Modeling and Forecasting in Business and Economics
Język
angielski
Rok wydania
1994
Oprawa
twarda
Liczba stron
625
ISBN10
0070349134
ISBN13
9780070349131
Seria
Tagi
Biznes
Ocena
4 z 5
Opis
This text is designed for forecasting courses in economics, management science and decision science departments, and emphasizing understanding and application rather than the theoretical and computational aspects of the statistical techniques used. Chapter 2 on describing and transforming data and chapter 9 on single equation econometric modelling offer in-depth discussions of topics fundamental to time-series analysis that most other texts cover in a cursory fashion. Appropriate to students with a minimal mathematics background (basic statistics and algebra), the text contains a review section on statistics and multiple regression and can be used effectively at both the graduate and undergraduate levels. The book's readibility is complemented by its inclusion of numerous visual aids such as graphs, tables and fully-worked examples. An ongoing case based on actual company data illustrates the use of important procedures described in each chapter. There is also in-depth coverage of popular computer software packages (for example, Lotus, MicroTSP, Minitab) including written programs and outputs. Two chapters on the Box-Jenkins procedure provide straightforward, intuitive, understandable coverage of a topic that is often difficult for students to grasp.