Ph.D. Preparation Program

Students who pursue the Ph.D. Preparation Program must take 9 credits from qualifying courses.

Required Courses (1 credit each for a total of 4 credits
BUAD 6329 - Introduction to Academic Research in Accounting

1 credit

 

Students will develop a framework for understanding scholarly research in accounting and will gain exposure to classic and current accounting research studies.

BUAD 6339 - Data and Analysis in Accounting Research

1 credit

 

Students will develop fundamental empirical skills, such as the use of databases and regression analysis. Applications will include the replication of a published accounting research study.

BUAD 6349 - Design of Accounting Research Studies

1 credit

 

Students will learn to apply the scientific method to accounting research questions by studying research designs used in scholarly accounting research and their effectiveness for causal inference. Applications will include addressing a research question using alternative designs.

BUAD 6359 - Current Research in Accounting

1 credit

 

Students read and discuss current academic research papers presented by William & Mary faculty and external accounting researchers. This course is open to any student interested in how research informs business practices and is well-suited for students considering careers in academia. Attendance at research presentations is required. Topics change each year so this course may be repeated once for credit.

Additional Credits
BUAD 6149 - Driving Organizational Performance

3 credits

 

This course will cover managerial accounting topics such as: customer lifetime estimation, cost of service delays, cost of quality analyses, time-driven Activity-Based-Costing, profit planning along the value chain, financial and operational forecasting, outsourcing, supplier choice and performance measurement, and analyses of profit drivers. This course replaces the Accounting for Business Strategies course, which met the cost credit requirement.

BUAD 6229 - Financial Statement Analysis

3 credits

 

This course introduces students to the elements of financial statement analysis and increases students' ability to extract and use information from financial reports. While financial statements are prepared in accordance with specific accounting rules and principles, most of the numbers in financial statements are based on a set of assumptions and choices made by management. In this class, students learn how to identify and adjust for the effects of accounting choices on the comparability of reported earnings and other accounting performance measures across countries, across firms, and over time. Students also learn how to evaluate circumstances where accounting rules can cause disruptions in trends making it difficult to forecast earnings and free cash flows. In addition, students learn techniques to identify earnings management, as well as assess whether the financial statements reflect the riskiness of the firm. Finally, because many large companies operate in a global environment, the class will examine problems created by differences in accounting standards across countries (e.g., U.S. Generally Accepted Accounting Principles versus International Financial Reporting Standards), as well as issues inherent in multinational companies such as how foreign currency affects financial statements.

BUAD 6249 - Data Analysis & Simulation for Accountants

3 credits

 

This course is designed to introduce students to basic modeling, analysis and simulation techniques. Emphasis will be placed on problem identification and formulation, sensitivity analysis, and model construction. Tools such as MS Excel, Solver, Crystal Ball, and @Risk will be used to solve accounting-related business problems.

CSCI 668 - Reliability

3 credits

 

Introduction to probabilistic models and statistical method used in analysis of reliability problems. Topics include models for the lifetime of a system of components and statistical analysis of survival times data. Problems will be solved using appropriate software tools.

MATH 524 - Operations Research: Stochastic Models

3 credits

 

A survey of probabilistic operations research models and applications. Topics include stochastic processes, Markov chains, queuing theory and applications, Markovian decision processes, inventory theory and decision analysis.

MATH 551 - Probability

3 credits

 

Topics include: combinational analysis, discrete and continuous probability distributions and characteristics of distributions, sampling distributions.

MATH 552 - Mathematical Statistics

3 credits

 

The mathematical theory of statistical inference. Possible topics include: maximum likelihood, least squares, linear models, methods for estimation and hypothesis testing.

Other electives may be taken and counted towards the Ph.D. preparation program with the approval of the Chair of the Accounting Department.