Buch, Englisch, 408 Seiten, Format (B × H): 179 mm x 253 mm, Gewicht: 764 g
Buch, Englisch, 408 Seiten, Format (B × H): 179 mm x 253 mm, Gewicht: 764 g
ISBN: 978-1-58488-495-8
Verlag: Taylor & Francis Inc
Business students need the ability to think statistically about how to deal with uncertainty and its effect on decision-making in business and management. Traditional statistics courses and textbooks tend to focus on probability, mathematical detail, and heavy computation, and thus fail to meet the needs of future managers.
Statistical Thinking in Business, Second Edition responds to the growing recognition that we must change the way business statistics is taught. It shows how statistics is important in all aspects of business and equips students with the skills they need to make sensible use of data and other information. The authors take an interactive, scenario-based approach and use almost no mathematical formulas, opting to use Excel for the technical work. This allows them to focus on using statistics to aid decision-making rather than how to perform routine calculations.
New in the Second Edition
- A completely revised chapter on forecasting
- Re-arrangement of the material on data presentation with the inclusion of histograms and cumulative line plots
- A more thorough discussion of the analysis of attribute data
- Coverage of variable selection and model building in multiple regression
- End-of-chapter summaries
- More end-of-chapter problems
- A variety of case studies throughout the book
The second edition also comes with a wealth of ancillary materials provided on downloadable resources packaged with the book. These include automatically-marked multiple-choice questions, answers to questions in the text, data sets, Excel experiments and demonstrations, an introduction to Excel, and the StiBstat Add-In for stem and leaf plots, box plots, distribution plots, control charts and summary statistics.
Zielgruppe
Undergraduate
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Variation. Problem Solving. Looking at Data. Modeling Data. Attribute Data. Sampling. Estimation. Regression Analysis. Multiple Regression. Forecasting. Statistical Process Control. Control Charts. Improvement Strategies. Postscript. Introduction to Excel.
