
Statistics for Business and Economics
Cengage Learning EMEA (Publisher)
3rd Edition
Published on 4. February 2014
Book
Paperback/Softback
672 pages
978-1-4080-7223-3 (ISBN)
Description
Clarity and cutting-edge examples have made Statistics for Business and Economics the definitive textbook for students across the United Kingdom, Europe, Middle East and Africa.
This new edition builds on the text's well-respected foundations to deliver a clear, up-to-date and comprehensive revision. All the key concepts, combined with the latest technologies and applications, are introduced with hallmark precision, making this your complete introduction to business statistics.
Clarity and cutting-edge examples have made Statistics for Business and Economics the definitive textbook for students across the United Kingdom, Europe, Middle East and Africa.
This new edition builds on the text's well-respected foundations to deliver a clear, up-to-date and comprehensive revision. All the key concepts, combined with the latest technologies and applications, are introduced with hallmark precision, making this your complete introduction to business statistics.
This new edition builds on the text's well-respected foundations to deliver a clear, up-to-date and comprehensive revision. All the key concepts, combined with the latest technologies and applications, are introduced with hallmark precision, making this your complete introduction to business statistics.
Clarity and cutting-edge examples have made Statistics for Business and Economics the definitive textbook for students across the United Kingdom, Europe, Middle East and Africa.
This new edition builds on the text's well-respected foundations to deliver a clear, up-to-date and comprehensive revision. All the key concepts, combined with the latest technologies and applications, are introduced with hallmark precision, making this your complete introduction to business statistics.
More details
Edition
3rd edition
Language
English
Place of publication
London
United Kingdom
Target group
College/higher education
Dimensions
Height: 260 mm
Width: 195 mm
Thickness: 20 mm
Weight
1090 gr
ISBN-13
978-1-4080-7223-3 (9781408072233)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Jim Freeman is Senior Lecturer in Statistics and Operational Research at Manchester Business School, United Kingdom. He has taught undergraduate and postgraduate courses in business statistics and operational research courses to students from a wide range of management and engineering backgrounds. For many years he was also responsible for providing introductory statistics courses to staff and research students at the University of Manchester's Staff Teaching Workshop. Through his gaming and simulation interests he has been involved in a significant number of external consultancy and grant-aided projects. More recently he received significant government (`KTP') funding for research in the area of risk management. In July 2008 he was Editor of the Operational Research Society's OR Insight journal. In November 2012 he received the Outstanding Achievement Award at the Decision Sciences Institute 43rd Annual Meeting in San Francisco. Eddie Shoesmith was formerly Senior Lecturer in Statistics and Programme Director for undergraduate business and management programmes in the School of Business, University of Buckingham, UK. At Buckingham, before joining the School of Business, he held posts as Dean of Sciences and Head of Psychology. He has taught introductory and intermediate-level applied statistics courses to undergraduate and postgraduate student groups in a wide range of disciplines: business and management, economics, accounting, psychology, biology and social sciences. He has also taught statistics to social and political sciences undergraduates at the University of Cambridge. Dr. Dennis J. Sweeney is a leading textbook author, Professor Emeritus of Quantitative Analysis, and founder of the Center for Productivity Improvement at the University of Cincinnati. He also served five years as head of the Department of Quantitative Analysis and four years as Associate Dean of the College of Business Administration. In addition, Dr. Sweeney has worked in the management science group at Procter & Gamble and has been a visiting professor at Duke University. Dr. Sweeney has published more than 30 articles in the area of management science and statistics. The National Science Foundation, IBM, Procter & Gamble, Federated Department Stores, Kroger, and Cincinnati Gas & Electric have funded his research, which has been published in Management Science, Operations Research, Mathematical Programming, Decision Sciences, and other respected journals. Dr. Sweeney is the co-author of ten textbooks in the areas of statistics, management science, linear programming, and production and operations management. Born in Des Moines, Iowa, he earned a B.S. degree from Drake University, graduating summa cum laude. He received his M.B.A. and D.B.A. degrees from Indiana University, where he was an NDEA Fellow. David R. Anderson is Professor of Quantitative Analysis in the College of Business Administration at the University of Cincinnati. Born in Grand Forks, North Dakota, he earned his BS, MS and PhD degrees from Purdue University. Professor Anderson has served as Head of the Department of Quantitative Analysis and Operations Management and as Associate Dean of the College of Business Administration. In addition, he was the coordinator of the college's first executive programme. Thomas A. Williams is Professor of Management Science in the College of Business at Rochester Institute of Technology (RIT). Professor Williams is the co-author of 11 textbooks in the areas of management science, statistics, production and operations management and mathematics. He has been a consultant for numerous Fortune 500 companies in areas ranging from the use of elementary data analysis to the development of large-scale regression models.
Jim Freeman is Senior Lecturer in Statistics and Operational Research at Manchester Business School, United Kingdom. He has taught undergraduate and postgraduate courses in business statistics and operational research courses to students from a wide range of management and engineering backgrounds. For many years he was also responsible for providing introductory statistics courses to staff and research students at the University of Manchester's Staff Teaching Workshop. Through his gaming and simulation interests he has been involved in a significant number of external consultancy and grant-aided projects. More recently he received significant government (`KTP') funding for research in the area of risk management. In July 2008 he was Editor of the Operational Research Society's OR Insight journal. In November 2012 he received the Outstanding Achievement Award at the Decision Sciences Institute 43rd Annual Meeting in San Francisco. Eddie Shoesmith was formerly Senior Lecturer in Statistics and Programme Director for undergraduate business and management programmes in the School of Business, University of Buckingham, UK. At Buckingham, before joining the School of Business, he held posts as Dean of Sciences and Head of Psychology. He has taught introductory and intermediate-level applied statistics courses to undergraduate and postgraduate student groups in a wide range of disciplines: business and management, economics, accounting, psychology, biology and social sciences. He has also taught statistics to social and political sciences undergraduates at the University of Cambridge. Dr. Dennis J. Sweeney is a leading textbook author, Professor Emeritus of Quantitative Analysis, and founder of the Center for Productivity Improvement at the University of Cincinnati. He also served five years as head of the Department of Quantitative Analysis and four years as Associate Dean of the College of Business Administration. In addition, Dr. Sweeney has worked in the management science group at Procter & Gamble and has been a visiting professor at Duke University. Dr. Sweeney has published more than 30 articles in the area of management science and statistics. The National Science Foundation, IBM, Procter & Gamble, Federated Department Stores, Kroger, and Cincinnati Gas & Electric have funded his research, which has been published in Management Science, Operations Research, Mathematical Programming, Decision Sciences, and other respected journals. Dr. Sweeney is the co-author of ten textbooks in the areas of statistics, management science, linear programming, and production and operations management. Born in Des Moines, Iowa, he earned a B.S. degree from Drake University, graduating summa cum laude. He received his M.B.A. and D.B.A. degrees from Indiana University, where he was an NDEA Fellow. David R. Anderson is Professor of Quantitative Analysis in the College of Business Administration at the University of Cincinnati. Born in Grand Forks, North Dakota, he earned his BS, MS and PhD degrees from Purdue University. Professor Anderson has served as Head of the Department of Quantitative Analysis and Operations Management and as Associate Dean of the College of Business Administration. In addition, he was the coordinator of the college's first executive programme. Thomas A. Williams is Professor of Management Science in the College of Business at Rochester Institute of Technology (RIT). Professor Williams is the co-author of 11 textbooks in the areas of management science, statistics, production and operations management and mathematics. He has been a consultant for numerous Fortune 500 companies in areas ranging from the use of elementary data analysis to the development of large-scale regression models.
Jim Freeman is Senior Lecturer in Statistics and Operational Research at Manchester Business School, United Kingdom. He has taught undergraduate and postgraduate courses in business statistics and operational research courses to students from a wide range of management and engineering backgrounds. For many years he was also responsible for providing introductory statistics courses to staff and research students at the University of Manchester's Staff Teaching Workshop. Through his gaming and simulation interests he has been involved in a significant number of external consultancy and grant-aided projects. More recently he received significant government (`KTP') funding for research in the area of risk management. In July 2008 he was Editor of the Operational Research Society's OR Insight journal. In November 2012 he received the Outstanding Achievement Award at the Decision Sciences Institute 43rd Annual Meeting in San Francisco. Eddie Shoesmith was formerly Senior Lecturer in Statistics and Programme Director for undergraduate business and management programmes in the School of Business, University of Buckingham, UK. At Buckingham, before joining the School of Business, he held posts as Dean of Sciences and Head of Psychology. He has taught introductory and intermediate-level applied statistics courses to undergraduate and postgraduate student groups in a wide range of disciplines: business and management, economics, accounting, psychology, biology and social sciences. He has also taught statistics to social and political sciences undergraduates at the University of Cambridge. Dr. Dennis J. Sweeney is a leading textbook author, Professor Emeritus of Quantitative Analysis, and founder of the Center for Productivity Improvement at the University of Cincinnati. He also served five years as head of the Department of Quantitative Analysis and four years as Associate Dean of the College of Business Administration. In addition, Dr. Sweeney has worked in the management science group at Procter & Gamble and has been a visiting professor at Duke University. Dr. Sweeney has published more than 30 articles in the area of management science and statistics. The National Science Foundation, IBM, Procter & Gamble, Federated Department Stores, Kroger, and Cincinnati Gas & Electric have funded his research, which has been published in Management Science, Operations Research, Mathematical Programming, Decision Sciences, and other respected journals. Dr. Sweeney is the co-author of ten textbooks in the areas of statistics, management science, linear programming, and production and operations management. Born in Des Moines, Iowa, he earned a B.S. degree from Drake University, graduating summa cum laude. He received his M.B.A. and D.B.A. degrees from Indiana University, where he was an NDEA Fellow. David R. Anderson is Professor of Quantitative Analysis in the College of Business Administration at the University of Cincinnati. Born in Grand Forks, North Dakota, he earned his BS, MS and PhD degrees from Purdue University. Professor Anderson has served as Head of the Department of Quantitative Analysis and Operations Management and as Associate Dean of the College of Business Administration. In addition, he was the coordinator of the college's first executive programme. Thomas A. Williams is Professor of Management Science in the College of Business at Rochester Institute of Technology (RIT). Professor Williams is the co-author of 11 textbooks in the areas of management science, statistics, production and operations management and mathematics. He has been a consultant for numerous Fortune 500 companies in areas ranging from the use of elementary data analysis to the development of large-scale regression models.
Author
Manchester Business School, UK
University of Buckingham, UK
University of Cincinnati
University of Cincinnati
Rochester Institute of Technology
Content
1. Data and Statistics
2. Descriptive Statistics: Tabular and Graphical Presentations
3. Descriptive Statistics: Numerical Measures
4. Introduction to Probability
5. Discrete Probability Distributions
6. Continuous Probability Distributions
7. Sampling and Sampling Distributions
8. Interval Estimation
9. Hypothesis Tests
10. Statistical Inference about Means and Proportions with Two Populations
11. Inferences about Population Variances
12. Tests of Goodness of Fit and Independence
13. Analysis of Variance and Experimental Design
14. Simple Linear Regression
15. Multiple Regression
16. Regression Analysis: Model Building
17. Time Series Analysis and Forecasting
18. Non-parametric Methods
2. Descriptive Statistics: Tabular and Graphical Presentations
3. Descriptive Statistics: Numerical Measures
4. Introduction to Probability
5. Discrete Probability Distributions
6. Continuous Probability Distributions
7. Sampling and Sampling Distributions
8. Interval Estimation
9. Hypothesis Tests
10. Statistical Inference about Means and Proportions with Two Populations
11. Inferences about Population Variances
12. Tests of Goodness of Fit and Independence
13. Analysis of Variance and Experimental Design
14. Simple Linear Regression
15. Multiple Regression
16. Regression Analysis: Model Building
17. Time Series Analysis and Forecasting
18. Non-parametric Methods