Statistics for Business
Pearson (Verlag)
978-0-13-449716-7 (ISBN)
- Titel erscheint in neuer Auflage
- Artikel merken
Understand Business. Understand Data.
The 3rd Edition of Statistics for Business: Decision Making and Analysis emphasizes an application-based approach, in which readers learn how to work with data to make decisions. In this contemporary presentation of business statistics, readers learn how to approach business decisions through a 4M Analytics decision making strategy–motivation, method, mechanics and message–to better understand how a business context motivates the statistical process and how the results inform a course of action. Each chapter includes hints on using Excel, Minitab Express, and JMP for calculations, pointing the reader in the right direction to get started with analysis of data.
Also available with MyLab Statistics
MyLab™ Statistics from Pearson is the world’s leading online resource for teaching and learning statistics; it integrates interactive homework, assessment, and media in a flexible, easy-to-use format. MyLab Statistics is a course management system that helps individual students succeed. It provides engaging experiences that personalize, stimulate, and measure learning for each student. Tools are embedded to make it easy to integrate statistical software into the course.
Note: You are purchasing a standalone product; MyLab™does not come packaged with this content. Students, if interested in purchasing this title with MyLab, ask your instructor for the correct package ISBN and Course ID. Instructors, contact your Pearson representative for more information.
If you would like to purchase both the physical text and MyLab, search for:
013450867X / 9780134508672 Statistics for Business: Decision Making and Analysis Plus MyLab Statistics with Pearson eText
Package consists of:
0134497163 / 9780134497167 Statistics for Business: Decision Making and Analysis
032192147X / 9780321921475 MyLab Statistics for Business Statistics -- Glue-In Access Card
0321929713 / 9780321929716 MyLab Statistics for Business Statistics Sticker
Robert Stine holds a Ph.D. from Princeton University. He has taught at the Wharton School since 1983, during which time he has regularly taught business statistics. During his tenure, Bob has received a variety of teaching awards, including regularly winning the MBA Core Teaching Award, which is presented to faculty for outstanding teaching of the required curriculum at Wharton. He also received the David W. Hauck Award for Outstanding Teaching, awarded to the most highly rated faculty member teaching in the Wharton undergraduate program. Bob actively consults for industry. His clients include the pharmaceutical firms Merck and Pfizer, and he regularly works with the Federal Reserve Bank of Philadelphia on models for retail credit risk. This collaboration has produced three well-received conferences held at Wharton. His areas of research include computer software, time series analysis and forecasting, and general problems related to model identification and selection. Bob has published numerous articles in research journals, including the Journal of the American Statistical Association, Journal of the Royal Statistical Society, Biometrika, and The Annals of Statistics. Dean Foster holds a Ph.D. from the University of Maryland. He has taught at the Wharton School since 1992 and previously taught at the University of Chicago. Dean teaches courses in introductory business statistics, probability and Markov chains, statistical computing and advanced statistics for managers. Dean’s research areas are statistical inference for stochastic processes, game theory, machine learning, and variable selection. He is published in a wide variety of journals, including The Annals of Statistics, Operations Research, Games and Economic Behaviour, Journal of Theoretical Population Biology, and Econometrica.
I. Variation
Introduction
Data
Describing Categorical Data
Describing Numerical Data
Association Between Categorical Variables
Association Between Quantitative Variables
II. Probability
Probability
Conditional Probability
Random Variables
Association Between Random Variables
Probability Models for Counts
The Normal Probability Model
III. Inference
Samples and Surveys
Sampling Variation and Quality
Confidence Intervals
Statistical Tests
Comparison
Inference for Counts
IV. Regression Models
Linear Patterns
Curved Patterns
The Simple Regression Model
Regression Diagnostics
Multiple Regression
Building Regression Models
Categorical Explanatory Variables
Analysis of Variance
Time Series
Supplementary Material (Online-Only) Alternative Approaches to Inference Two-Way Analysis of Variance Regression with Big Data
| Erscheinungsdatum | 01.03.2017 |
|---|---|
| Sprache | englisch |
| Maße | 222 x 277 mm |
| Gewicht | 1910 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik |
| Mathematik / Informatik ► Mathematik ► Statistik | |
| ISBN-10 | 0-13-449716-3 / 0134497163 |
| ISBN-13 | 978-0-13-449716-7 / 9780134497167 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
