Cleff, Thomas.
Exploratory Data Analysis in Business and Economics An Introduction Using SPSS, Stata, and Excel / [electronic resource] : by Thomas Cleff. - XXII, 215 p. 130 illus., 11 illus. in color. online resource.
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. .
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.
9783319015170
10.1007/978-3-319-01517-0 doi
Statistics.
Mathematical statistics.
Statistics.
Statistics for Business/Economics/Mathematical Finance/Insurance.
Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law.
Probability and Statistics in Computer Science.
QA276-280
330.015195
Exploratory Data Analysis in Business and Economics An Introduction Using SPSS, Stata, and Excel / [electronic resource] : by Thomas Cleff. - XXII, 215 p. 130 illus., 11 illus. in color. online resource.
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. .
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.
9783319015170
10.1007/978-3-319-01517-0 doi
Statistics.
Mathematical statistics.
Statistics.
Statistics for Business/Economics/Mathematical Finance/Insurance.
Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law.
Probability and Statistics in Computer Science.
QA276-280
330.015195