Awarded Outstanding Academic Book by CHOICE magazine in its first edition, FORECASTING, TIME SERIES, AND REGRESSION: AN APPLIED APPROACH now appears in a fourth edition that illustrates the vital importance of forecasting and the various statistical techniques that can be used to produce them. With an emphasis on applications, this book provides both the conceptual development and practical motivation students need to effectively implement forecasts of their own. Bruce Bowerman, Richard O'Connell, and Anne Koehler clearly demonstrate the necessity of using forecasts to make intelligent decisions in marketing, finance, personnel management, production scheduling, process control, and strategic management. In addition, new technology coverage makes the latest edition the most applied text available on the market.
This comprehensive book introduces students to time series and forecasting techniques. The prerequisites are college algebra and basic statistics. It contains complete coverage of linear regression analysis, which provides much...
Forecasting and multiple regression analysis; Forecasting time series described by trend and irregular components; Forecasting seasonal time series; The box-jenkins methodology.
Forecasting is required in many situations.
The book introduces popular forecasting methods and approaches used in a variety of business applications. The book offers clear explanations, practical examples, and end-of-chapter exercises and cases.
The book is also an excellent reference for practitioners and researchers who need to model and analyze time series data to generate forecasts.
This practical, user-oriented second edition describes how to use statistical modeling and analysis methods for forecasting and prediction problems. Statistical and mathematical terms are introduced only as they are needed,...
This is the first book on applied econometrics using the R system for statistical computing and graphics.
Time Series Forecasting: Unified Concepts and Computer Implementation
Providing a clear explanation of the fundamental theory of time series analysis and forecasting, this book couples theory with applications of two popular statistical packages--SAS and SPSS.
The book presents methodologies for time series analysis in a simplified, example-based approach.