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Exploratory Data Analysis in Business and Economics: An Introduction Using SPSS, Stata, and Excel

Autor Thomas Cleff
en Limba Engleză Paperback – 25 noi 2013
In a world in which we are constantly surrounded by data, figures, and statistics, it is imperative to understand and to be able to use quantitative methods. Statistical models and methods are among the most important tools in economic analysis, decision-making and business planning. This textbook, “Exploratory Data Analysis in Business and Economics”, aims to familiarise students of economics and business as well as practitioners in firms with the basic principles, techniques, and applications of descriptive statistics and data analysis. Drawing on practical examples from business settings, it demonstrates the basic descriptive methods of univariate and bivariate analysis. The textbook covers a range of subject matter, from data collection and scaling to the presentation and univariate analysis of quantitative data, and also includes analytic procedures for assessing bivariate relationships. It does not confine itself to presenting descriptive statistics, but also addresses the use of computer programmes such as Excel, SPSS, and STATA, thus treating all of the topics typically covered in a university course on descriptive statistics. The German edition of this textbook is one of the “bestsellers” on the German market for literature in statistics.
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Specificații

ISBN-13: 9783319015163
ISBN-10: 3319015168
Pagini: 280
Ilustrații: XXII, 215 p. 130 illus., 11 illus. in color.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.34 kg
Ediția:2014
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland

Public țintă

Upper undergraduate

Cuprins

Statistics and Empirical Research.- From Disarray to Dataset.- Univariate Data Analysis.- Bivariate Association.- Regression Analysis.- Time Series and Indices.- Cluster Analysis.- Factor Analysis.- Solutions to Chapter Exercises.- References and Bibliography.- Index.

Notă biografică

Thomas Cleff is a Professor of Quantitative Methods for Business & Economics at Pforzheim University and a research associate at the Mannheim Centre for European Research (ZEW). He has served as a visiting professor at several renowned international universities - Ecole de Management ESCEM Tours-Poitiers; Simon Fraser University Vancouver; TEC de Monterrey, and Universitas Gadjah Mada Yogyakarta.

Textul de pe ultima copertă

In a world in which we are constantly surrounded by data, figures, and statistics, it is imperative to understand and to be able to use quantitative methods. Statistical models and methods are among the most important tools in economic analysis, decision-making and business planning. This textbook, “Exploratory Data Analysis in Business and Economics”, aims to familiarise students of economics and business as well as practitioners in firms with the basic principles, techniques, and applications of descriptive statistics and data analysis. Drawing on practical examples from business settings, it demonstrates the basic descriptive methods of univariate and bivariate analysis. The textbook covers a range of subject matter, from data collection and scaling to the presentation and univariate analysis of quantitative data, and also includes analytic procedures for assessing bivariate relationships. It does not confine itself to presenting descriptive statistics, but also addresses the use of computer programmes such as Excel, SPSS, and STATA, thus treating all of the topics typically covered in a university course on descriptive statistics. The German edition of this textbook is one of the “bestsellers” on the German market for literature in statistics.

Caracteristici

An “easy to understand” textbook including numerical examples Includes analytic procedures for assessing bivariate relationships Provides readers with an understanding of the thinking processes underlying descriptive statistics Addresses the use of computer programmes such as Excel, SPSS, and STATA Problems and solutions at the end of each chapter to pursue effective self-study Includes supplementary material: sn.pub/extras