Auditing after Sarbanes Oxley or Basic Statistical Ideas for Managers

Auditing after Sarbanes-Oxley: Illustrative Cases

Author: Jay C Thibodeau

This casebook is intended as a supplement to any primary auditing text, as it helps extend and focus classroom discussions on the impact of Sarbanes-Oxley. It grabs student interest by providing engaging, real- world examples of the auditing environment pre- and post-Sarbanes-Oxley.
The text presents a total of 35 "ripped from the headlines" cases organized within four sections:
1) Ethics and Professional Responsibility (7 cases),
2) Understanding the Client's Business and Industry (7 cases),
3) Internal Control Systems (10 cases),
4) Audits of Accounts, Processes and Assertions (11 Cases).
This organization closely follows that of most current auditing textbooks, making the cases easy to implement.
In addition to these cases, Appendix A presents seven lengthier, complete company cases giving instructors the flexibility to assign a single case to cover several learning objectives. Appendix B presents financial statements for four of the companies covered in Appendix A.

Go to: The Psychology Majors Handbook or Understanding Financial Crises

Basic Statistical Ideas for Managers (with CD-ROM)

Author: David Hildebrand

Designed for the one-term MBA or undergraduate introduction to business statistics course, this text places emphasis on data and the common techniques and methods used to analyze them in business. It introduces concepts using practical examples and illustrates them with computer output from MINITAB, Excel, and JMP. The book integrates a business decision-making case into each chapter for motivational and illustration purposes and includes a business case assignment at the end of each chapter. These cases revolve around realistic business settings with realistic data sets that put students in the role of managers who need to make business decisions based on data. Review problems requiring students to use previously learned concepts also appear throughout to promote understanding of the relationships among statistical methods.

Table of Contents:

1	Making sense of data	1
2	Summarizing data	11
3	A First look at probability	81
4	Random variables and probability distributions	131
5	Some special probability distributions	171
6	Random sampling and sampling distributions	215
7	Point and interval estimation	253
8	Hypothesis testing	305
9	Comparing two samples	353
10	Analysis of variance and designed experiments	421
11	Linear regression and correlation methods	495
12	Multiple regression methods	567
13	Construction a multiple regression model	617