Author Profile

Dr. Petr Rozehnal is a pioneering scholar and academic at the Faculty of Economics (business and management), specializing in IT governance, business-IT alignment, and virtual reality (VR) in education. He bridges theoretical management with immersive tech to prepare students for themodern digital economy. His academic journey blends data science with practical business strategy. Beyond traditional academia, he is celebrated for developing interactive VR university modules, such as 3-D educational rooms for finance and marketing. He has published vital research on integrating IT governance models (such as COBIT) into small and medium-sized enterprises. He co-authored in-depth studies evaluating the use of statistical and hybrid forecasting models in real-world business practice. Along with colleagues, he has explored how "desktop VR" paradigms can act as a facilitator to strengthen students' learning retention and analytical skills. Dr. Petr Rozehnal sits at the crossroads where raw data meets corporate strategy. Inside his office at the Faculty of Economics, the chalkboard is rarely covered in traditional financial formulas. Instead, it features intricate maps of information fiows, cloud architecture schemas, and predictive hybrid demand forecasting models. To him, modern business commerce is no longer just about buying and selling; it is an interconnected ecosystem driven by digital infrastructure. The book stems from a simple, frustrating observation: business students frequently graduate understanding economic theory, but crumble when managing actual corporate IT frameworks. Dr. Rozehnal wrote this definitive text to bridge that exact gap. He integrated complex topics like Business Process Management (BPM) and COBIT IT Governance into a highly readable masterclass for the next generation of commerce leaders.

About The Book

Quantitative Methods for Business bridges academic theory and real-world corporate application. This book provides a clear, comprehensive guide to the essential mathematical and statistical tools required in modern commerce. It transforms dense mathematical formulas into accessible, practical frameworks for students and practicing managers alike. This book demystifies quantitative analysis by focusing on logic, application, and interpretation rather than raw calculation. Every chapter grounds complex methodologies in actual corporate scenarios. Readers will learn not just how to compute a number, but what that number means for operational strategy, financial risk, and market positioning. This book, Quantitative Methods for Business, bridges the gap between raw data and actionable strategy. It equips modern managers and students with the core mathematical, statistical, and programming tools required to transform complex datasets into clear, evidence-based business decisions. Designed for both academic and practical application, the text breaks down advanced analytical frameworks into an accessible, step-by-step format. The text describes the many quantitative methods developed over the years, explains how they work, and shows how the decision maker can apply and interpret them. This book is written with the nonmathematician in mind.

Table of Contents

Preface
CHAPTER 1 Quantitative Techniques
Meaning And Definition
Mathematical Quantitative Techniques
Statistical Quantitative Techniques
Programming Techniques
Uses of Quantitative Techniques
CHAPTER 2 Correlation Analysis
Introduction
Significance of Correlation Analysis
Methods of Measuring Correlation
CHAPTER 3 Quantitative Approach To Decision Making
Model Classifications
Linear Programming Models
Minimization Models
CHAPTER 4 Probability
Introduction
Experiment, Sample Space, Event
Different Approaches To Probability Theory
Calculating Probabilities In Complex Situations
Revising Probability Estimate
Summary
CHAPTER 5 Hypothesis Testing
Introduction
Concept And Meaning
Importance of Hypothesis In Marketing Research
Concept of Hypothesis Testing
Process of Hypothesis Testing
Use of Spss For Hypothetical Case Analysis
Summary
CHAPTER 6 Chi-Square Test
Chi-Square Distribution
Chi-Square Distribution
Chi-Square Test For Independence of Attributes
Chi-Square Test For Goodness of Fit
Conditions For Applying Chi-Square Test
Cells Pooling
Yates Correction
Limitations of Chi-Square Test
CHAPTER 7 The Inventory Model
The Economic Order Quantity (EOQ) Model
The Optimal Order Quantity Model
Inventory With Planned Shortage
CHAPTER 8 Correlation
Introduction
Concept of Correlation, Direction And Magnitude of Correlation
Properties, Uses And Limitations of Correlation
Other Methods of Correlation
Computation of Coefficient of Correlation
Pearson’s Product Moment Correlation
Spearman’s Rank Order Correlation
CHAPTER 9 Dynamic Techniques
Definite And Indefinite Integration
First-Order Linear Difference Equations
Second-Order Linear Difference Equations
First-Order Linear Differential Equations
Second-Order Linear Differential Equations
CHAPTER 10 Linear Programming I: The Simplex Method
A Problem’s Formulation And Assumptions
Graphical Solution of Linear Programming Problems
The Simplex Method: Maximization Problems
The Simplex Method: Minimization Problems
CHAPTER 11 Linear Programming II: Sensitivity Analysis, Duality, And Integer Programming
Sensitivity Analysis
Duality
Integer Programming
CHAPTER 12 Decision Analysis
Formulation of Decision Problems
Decision Making Under Various Conditions
Utility And Decision Making
Derivation of The Utility Function
CHAPTER 13 Game Theory
Concepts And Problem Formulation
Solving Zero-Sum Games
Nonzero-Sum Games
The Prisoner’s Dilemma
Bibliography
Index