Introduction
Welcome to Intermediate Managerial Accounting: Mastery Through Practice! This book is designed to help you learn more complex managerial accounting methods than those taught in introductory managerial accounting courses in a methodical, step-by-step manner. Each chapter is organized as follows:
Objectives:
On the title page of each chapter, you’ll find a list of learning objectives expressing what students should be able to do after studying the material in the chapter.
In each chapter, one to two pages of text explain the theory behind the methods you will learn. This is a bare-bones summary of the theory and, along with the method section, is the very minimum you should read.
This section outlines the methods taught in each chapter in one to two pages.
Example:
This section walks through the methods outlined in the method section using a complete example.
Problem:
You should practice the methods for the first time using this problem, which allows you to check your work periodically as the problem progresses.
Exercises:
This section includes exercises that may be used by your instructor during their lecture.
Exercises:
These short exercises focus on each step in the method, one step at a time, so that you can build your skills gradually.
Problems:
These complete problems require you to use the methods in their entirety.
Problem:
This problem may be assigned by your instructor as homework to be turned in or as an in-class exercise.
Problem:
This problem is intended to be very complex. Students who want a challenge can try it—if you dare!
Assessment
Problem:
This problem is intended for you to use as one final practice before taking your assessment. Don’t use the book or your notes—treat this like it’s a real assessment!
Any terminology introduced in the chapter is defined in this section.
Acknowledgments
ChatGPT was used to help generate and test exercises and problems and generate alt-text for images in this book. The author takes full responsibility for all content developed with the assistance of artificial intelligence.
Many thanks to Gavin Neugart, Kristen Neumann, Sue Ravenscroft, Mike Bootsma, Diane Janvrin, Winston Chappell, Ting Li Zhou, Laura Enderson, Marina Auwerda, Waylon Sternhagen, and Rachel Ellefson for feedback and for testing these materials.
