Statistical Techniques for Forensic Accounting Understanding the Theory and Application of Data Analysis

  • ISBN13:


  • ISBN10:


  • Edition: 1st
  • Format: Hardcover
  • Copyright: 2013-06-18
  • Publisher: FT Press

Note: Supplemental materials are not guaranteed with Rental or Used book purchases.

Purchase Benefits

  • Free Shipping On Orders Over $35!
    Your order must be $35 or more to qualify for free economy shipping. Bulk sales, PO's, Marketplace items, eBooks and apparel do not qualify for this offer.
  • Get Rewarded for Ordering Your Textbooks! Enroll Now
List Price: $89.99 Save up to $18.00
  • Rent Book $71.99
    Add to Cart Free Shipping


Supplemental Materials

What is included with this book?

  • The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.
  • The Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.


Master powerful statistical techniques for uncovering fraud or misrepresentation in complex financial data.The discipline of statistics has developed sophisticated, well-accepted approaches for identifying financial fraud and demonstrating that it is deliberate. Statistical Techniques for Forensic Accountingis the first comprehensive guide to these tools and techniques. Leading expert Dr. Saurav Dutta explains their mathematical underpinnings, shows how to use them properly, and guides you in communicating your findings to other interested and knowledgeable parties, or assessing others'analyses. Dutta is singularly well-qualified to write this book: he has been engaged as an expert in many of the world's highest-profile financial fraud cases, including Worldcom, Global Crossing, Cendant, and HealthSouth. Here, he covers everything professionals need to know to construct and conduct valid and defensible statistical tests, perform analyses, and interpret others'analyses. Coverage includes: exploratory data analysis to identify the "Fraud Triangle" and other red flags… data mining tools, usage, and limitations… statistical terms and methods applicable to forensic accounting… relevant uncertainty and probability concepts… Bayesian analysis and networks… statistical inference, sampling, sample size, estimation, regression, correlation, classification, prediction, and much more. For all forensic accountants, auditors, investigators, and litigators involved with corporate financial reporting; and for all students interested in forensic accounting and related fields.

Author Biography

SAURAV DUTTA (Albany, NY) is Associate Professor and former chair of the Department of Accounting, Business Law and Taxation at Univ. of Albany. In 2011, he served as Academic Fellow in the SEC's Office of Chief Accountant. Dutta's research interests are in applying statistical and analytical methodologies to accounting and auditing. He has published 20+ research papers, and conducted seminars at universities including Harvard, Oxford, NYU, and Maastricht. Invited by AICPA to present on statistics for forensic accounting and litigation, he has been engaged as an expert to design statistical procedures to verify claims against Worldcom, Global Crossing, Cendant, GM, and HealthSouth.

Table of Contents

1. Introduction to Forensic Accounting and Fraud Detection

2. Fraudulent Financial Reporting

3. The Fraud Triangle and Other Red Flags

4. Prevention of Fraud, Corporate Governance and Internal Controls

5. Detection of Fraud, Shared Responsibility

6. Data Mining

7. Qualitative Characteristic of Evidence

8. Data Types and Probability

9. Continuous Probability Distribution and their Properties

10. Statistical Inference

11. Sampling and Sample Size Determination

12. Statistical Estimation

13. Auditor Decision and Risk of Error

14. Fundamentals of Hypotheses Testing

15. Regression and Correlation

16. Time Series Analysis ( To be decided upon further consultation)

17. Classification and Prediction

Rewards Program

Write a Review