Description

Book Synopsis
This book is written for business persons who wish to forecast consumer demands and sales. It is also designed for economic, financial, governmental, and private practitioners, who make decisions based on costs, benefits, economic trends, and growth. Finally, the book is written for first year MBA students, undergraduate students, and other readers who wish to acquire a fundamental knowledge of forecasting for the purpose of pursuing jobs in the fields of economics and finance, or for making personal plans for the future.

The book emphasizes applied aspects of forecasting rather than theoretical aspects, so a working knowledge of high-school statistics and college algebra is all the mathematics that is needed. Because regression-based forecasts do not appear until the last three chapters of the book, knowledge of econometrics or time-series modeling is not a prerequisite. Additionally, although each chapter is designed to be self-explanatory, a basic understanding of econometrics might be helpful, but not necessary.

The book discusses most of the forecasting methods frequently used in business and economics, such as time-series, demand and sales, investment, short-term planning, long-term growth, and regressions. To keep the book concise, only a brief introduction to the ARIMA process is introduced. Readers who wish to gain in-depth knowledge of ARIMA models are encouraged to read a book written specifically for time-series modeling.

Seeing the Future: How to Build Basic Forecasting Models

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    Order before 4pm today for delivery by Sat 20 Jun 2026.

    A Paperback by Tam Bang Vu


      View other formats and editions of Seeing the Future: How to Build Basic Forecasting Models by Tam Bang Vu

      Publisher: Business Expert Press
      Publication Date: 30/04/2015
      ISBN13: 9781606497906, 978-1606497906
      ISBN10: 1606497901

      Description

      Book Synopsis
      This book is written for business persons who wish to forecast consumer demands and sales. It is also designed for economic, financial, governmental, and private practitioners, who make decisions based on costs, benefits, economic trends, and growth. Finally, the book is written for first year MBA students, undergraduate students, and other readers who wish to acquire a fundamental knowledge of forecasting for the purpose of pursuing jobs in the fields of economics and finance, or for making personal plans for the future.

      The book emphasizes applied aspects of forecasting rather than theoretical aspects, so a working knowledge of high-school statistics and college algebra is all the mathematics that is needed. Because regression-based forecasts do not appear until the last three chapters of the book, knowledge of econometrics or time-series modeling is not a prerequisite. Additionally, although each chapter is designed to be self-explanatory, a basic understanding of econometrics might be helpful, but not necessary.

      The book discusses most of the forecasting methods frequently used in business and economics, such as time-series, demand and sales, investment, short-term planning, long-term growth, and regressions. To keep the book concise, only a brief introduction to the ARIMA process is introduced. Readers who wish to gain in-depth knowledge of ARIMA models are encouraged to read a book written specifically for time-series modeling.

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