The time value of money; valuation of financial securities; allocating capital; an introduction to risk and risky decision making; the financing decision of the firm; financial statement and working capital management; more special topics include mergers and acquisitions, and international finance. Prerequisite: ACCOUNTG 221

Concentration on the federal income taxation of corporations, partnerships, estates and trusts, gifts and estate taxes.

Continuation of ACCOUNTG 321. Conceptual framework for accounting for a firm's reported liabilities. The nature of liabilities, their recognition, measurement, and disclosure. Motivation of management in choosing among acceptable accounting alternatives in each of these areas, and the economic choices of such consequences. Prerequisite: ACCOUNTG 321. (Those who did not receive at least C should seriously consider taking that course over, prior to enrollment in ACCOUNTG 322.)

This course introduces fundamental concepts and computations for statistical analysis of business data and real-world problems with an emphasis on understanding and interpreting statistical information, and using it to form sound judgments in business situations. The course covers basic descriptive statistical methods, sampling methodology, how to draw inferences from samples to larger populations and how to make predictions based upon historical relationships between variables. Theoretical background in descriptive and inferential statistical methods will be used support knowledge of the appropriate statistical test to perform in a given situation. The statistical methods that are covered in the course equip the student with the analytic reasoning and quantitative arguments that applies to all areas of business and management.

Examines representing, capturing, and reporting of information about events relevant to the operations of a business organization. The course also uses various data analytics approaches to analyze the efficiency, effectiveness, and control of business processes. Controls over business operations are examined from a number of different perspectives including COSO and CoBIT.

This course provides an introduction to topics in managerial data mining, and related data retrieval and manipulation content. Models in regression, clustering, neural nets, classification, and association rule mining are applied to business data sets. In this managerially-focused course, students will learn how to use such models and interpret output. Students will also be introduced to a programming language for extraction and manipulation of data. Experiential exercises will be assigned using leading industry applications.

An overview of the concepts and language of financial and managerial accounting that covers how accounting information can be used as an effective tool for communication, monitoring, and resource allocation. Topics include the principles and methodologies underlying financial statements and the inherent limitations of that information. Additional topics include behavior, cost analysis, and tools used to motivate and coordinate business activities.

This course provides an introduction to Business Intelligence, including the processes, methodologies, infrastructure, and current practices used to transform business data into useful information and support business decision-making. Business Intelligence requires foundation knowledge in data storage and retrieval, thus this course will review logical data models for both database management systems and data warehouses. Students will learn to extract and manipulate data from these systems and assess security-related issues. Data mining, visualization, and statistical analysis along with reporting options such as management dashboards and balanced scorecards will be covered.

This course provides an introduction to Business Intelligence, including the processes, methodologies, infrastructure, and current practices used to transform business data into useful information and support business decision-making. Business Intelligence requires foundation knowledge in data storage and retrieval, thus this course will review logical data models for both database management systems and data warehouses. Students will learn to extract and manipulate data from these systems and assess security-related issues. Data mining, visualization, and statistical analysis along with reporting options such as management dashboards and balanced scorecards will be covered.

Course will address the needs of students considering starting their own business or purchasing and managing a business or franchise. Areas to be covered during the class are as follows: Idea generation ? differentiate or die; discuss the importance of ?differentiation? and why most new businesses underestimate this critical concept. Choosing the appropriate business structure: Limited Liability Company, Subchapter C Corporation, Subchapter S Corporation. Developing the business plan: gathering and preparing the proper information to attract financing. Funding your business: identifying sources of funding such as Venture Capital, Private Equity, partners, lenders. Human resources: hiring your first employee, evaluating potential sales people, choosing incentive programs. Successful marketing strategies: numerous examples of creative and effective marketing decisions propelling companies forward. Successful sales strategies: numerous examples of tactics designed to get consumers to buy. Exit strategies: selling to private firms, going public, maintaining partial ownership while remaining in management.