Anderson D. Statistics for Business and Economics 5ed 2020
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Anderson D. Statistics for Business and Economics 5ed 2020
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Textbook in PDF format
The purpose of Statistics for Business and Economics is to give students, primarily those in the fields of business, management and economics, a conceptual introduction to the field of statistics and its many applications. The text is applications-oriented and written with the needs of the non-mathematician in mind. The mathematical prerequisite is knowledge of algebra. Applications of data analysis and statistical methodology are an integral part of the organization and presentation of the material in the text. The discussion and development of each technique are presented in an application setting, with the statistical results providing insights to problem solution and decision-making. Although the book is applications-oriented, care has been taken to provide sound methodological development and to use notation that is generally accepted for the topic being covered. Hence, students will find that this text provides good preparation for the study of more advanced statistical material. A revised and updated bibliography to guide further study is included as an appendix.
The EMEA Edition
This is the 5th. EMEA edition of Statistics for Business and Economics. It is based on the 4th EMEA edition and the 13th. United States (US) edition. The US editions have a distinguished history and deservedly high reputation for clarity and soundness of approach. We have aimed to maintain the style and readability of those editions, whilst recognizing that the EMEA edition is intended for students in many parts of the world, many of whom do not have English as a first language. We have replaced most of the US-based examples, case studies and exercises with equally interesting and appropriate ones sourced from a wider geographical base, particularly the UK, Ireland, continental Europe, South Africa and the Middle East. Other notable changes in this 5th EMEA edition are summarized here:
Case Problems, exercises and Statistics in Practice features have been updated throughout to relate statistics to current issues and bring concepts alive.
The section on data mining in Chapter 1 has been expanded to include a discussion on big data and a new section on analytics has been added. The distinction between observed and experimental data has been highlighted.
Chapter 5 has been expanded to allow for new material on bivariate distributions, covariance and financial applications.
Examples have been added to Chapter 12 in particular to point out an alternative computational method for calculating the chi-squared statistic in goodness-of-fit tests.
Preface.
Acknowledgements.
About the authors.
Data and statistics.
Descriptive statistics: tabular and graphical presentations.
Descriptive statistics: numerical measures.
Introduction to probability.
Discrete probability distributions.
Continuous probability distributions.
Sampling and sampling distributions.
Interval estimation.
Hypothesis tests.
Statistical inference about means and proportions with two populations.
Inferences about population variances.
Tests of goodness of fit and independence.
Experimental design and analysis of variance.
Simple linear regression.
Multiple regression.
Regression analysis: model building.
Time series analysis and forecasting.
Non-parametric methods.
Appendix A: References and bibliography.
Appendix B: Tables.
Glossary.
Credits.
Index