Statistical Modeling for Management
If you’re in North America, please visit our Sage College Publishing website to purchase or sample this book:
Go to College Publishing WebsiteDescription
The process of making marketing decisions is increasingly dependent on quantitative analysis and the use of specific statistical tools and techniques which can be tailored and adapted to solve particular marketing problems.
Any student hoping to enter the world of management will need to show that they understand and have mastered these techniques. This book will help them to do this and covers the following key topics:
- Measurement sacling and reliability issues in management
- Parametric and non-parametric statistical tests
- Gerneralized Linear Modeling techniques
- Data-reduction techniques
- Model selection and model checking
- Recursive and non-recursive models
- Neural networks
- Knowledge-based systems
This book is ideal for students taking upper level undergraduate classes and graduate classes in statistics for business and management.
Contents
Measurement Scales
Measurement Scales
Modeling Continuous Data
Modeling Continuous Data
Modeling Dichotomous Data
Modeling Dichotomous Data
Modeling Ordered Data
Modeling Ordered Data
Modeling Unordered Data
Modeling Unordered Data
Neural Networks
Neural Networks
Approximate Algorithms for Management Problems
Approximate Algorithms for Management Problems
Other Statistical, Mathematical and Co-pattern Modeling Techniques
Other Statistical, Mathematical and Co-pattern Modeling Techniques
Description
The process of making marketing decisions is increasingly dependent on quantitative analysis and the use of specific statistical tools and techniques which can be tailored and adapted to solve particular marketing problems.
Any student hoping to enter the world of management will need to show that they understand and have mastered these techniques. This book will help them to do this and covers the following key topics:
- Measurement sacling and reliability issues in management
- Parametric and non-parametric statistical tests
- Gerneralized Linear Modeling techniques
- Data-reduction techniques
- Model selection and model checking
- Recursive and non-recursive models
- Neural networks
- Knowledge-based systems
This book is ideal for students taking upper level undergraduate classes and graduate classes in statistics for business and management.
Contents
Measurement Scales
Measurement Scales
Modeling Continuous Data
Modeling Continuous Data
Modeling Dichotomous Data
Modeling Dichotomous Data
Modeling Ordered Data
Modeling Ordered Data
Modeling Unordered Data
Modeling Unordered Data
Neural Networks
Neural Networks
Approximate Algorithms for Management Problems
Approximate Algorithms for Management Problems
Other Statistical, Mathematical and Co-pattern Modeling Techniques
Other Statistical, Mathematical and Co-pattern Modeling Techniques
March 2008 | 256 pages | Sage UK
| Format | Published Date | ISBN | Price |
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The process of making marketing decisions is increasingly dependent on quantitative analysis and the use of specific statistical tools and techniques which can be tailored and adapted to solve particular marketing problems.
Any student hoping to enter the world of management will need to show that they understand and have mastered these techniques. This book will help them to do this and covers the following key topics:
- Measurement sacling and reliability issues in management
- Parametric and non-parametric statistical tests
- Gerneralized Linear Modeling techniques
- Data-reduction techniques
- Model selection and model checking
- Recursive and non-recursive models
- Neural networks
- Knowledge-based systems
This book is ideal for students taking upper level undergraduate classes and graduate classes in statistics for business and management.
Table Of Contents:
- Measurement Scales
- Modeling Continuous Data
- Modeling Dichotomous Data
- Modeling Ordered Data
- Modeling Unordered Data
- Neural Networks
- Approximate Algorithms for Management Problems
- Other Statistical, Mathematical and Co-pattern Modeling Techniques