Quantitative Methods for Business by David R. Anderson, Dennis J. Sweeny, Thomas A. Williams, Jeff D. Camm & R. Kipp Martin is a textbook focusing on the role quantitative methods play in the decision making process. The authors have done a great job in making Quantitative Methods for Business user friendly and explanatory. Quantitative Methods for Business describes quantitative methods thoroughly and explains how it works to a great extend! Quantitative Methods for Business shows how the decision maker can apply & interpret the methods.
Graduate Tutor’s Tutor group uses Quantitative Methods for Business for most Statistics related topics as seen in MBA programmes.
Statistics courses have high priority in B Schools & Graduate Schools as its knowledge is essential for business & data analysis. Quantitative Methods for Business enables you fasten your basics and get a hang of business school statistics.
Into its eleventh edition, Quantitative Methods for Business continued to be one of the most sought after textbook in its spectrum. Quantitative Methods for Business has made the following changes in the eleventh edition
- New Chapter 12: Advanced Optimization Applications
- New Documented Solutions
- New Appendix A: Building Spreadsheet Models
- Updated Chapter 10: Distribution and Network Models
- New Q.M in Action, Cases, and Problems
Graduate Tutor offers a wide array of tutoring options for business executives and MBA students to develop their Statistics knowledge. Quantitative Methods for Business is the most sought after textbook for statistics tutoring at Graduate tutor.
The content covered in Quantitative Methods for Business by David R. Anderson, Dennis J. Sweeny, Thomas A. Williams, Jeff D. Camm, R. Kipp Martin includes:
- Introduction To Probability
- Probability Distributions
- Decisions Analysis
- Utility And Game Theory
- Introduction To Linear Programming
- Linear Programming: Sensitivity Analysis And Interpretation Of Solution
- Linear Programming Applications In Marketing, Finance And Operations Management
- Distribution And Network Models
- Integer Linear Programming
- Advanced Optimization Applications
- Project Scheduling: PERT/CPM
- Inventory Models
- Waiting Line Models
- Markov Processes
- Building Spreadsheet Models
- Binomial Probabilities