Managerial accounting
Whitecotton, Stacey (penulis) ; Libby, Robert (penulis) ; Philips, Fred (penulis)
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Deskripsi
Indeks : halaman 541 ; Whitecotton, Managerial Accounting 2e and Connect present an integrated and proven solution designed to help attain course goals of student readiness and motivation, comprehension of content, and application of key concepts. Whitecotton, Managerial Accounting 2e addresses the reality of students taking the managerial accounting course: the majority of them will not become accounting majors and accountants; instead they will use accounting information in their professional lives to make business decisions. Therefore, the greatest challenges instructors have are to engage these students in the managerial accounting course, keep the students motivated throughout the course, and teach them accounting in a way that connects conceptual understanding to the real world, so students will be able to analyze and apply their managerial accounting knowledge successfully in careers as managers in the world of business. Whitecotton 2e will engage and motivate students by presenting accounting in the context of real, recognizable companies like Apple, Starbucks, and California Pizza Kitchen, then integrate those companies throughout the chapters. This will allow students to see accounting information being used to make real business decisions in companies that are part of their lives, helping them connect their learning to the real world. McGraw-Hill Connect Accounting Plus provides a complete digital solution with a robust online learning and homework management system, an integrated media-rich eBook, assignable end-of-chapter material, algorithmic functionality, and reporting capabilities. Contained within Connect Accounting is McGraw-Hill’s adaptive learning system, LearnSmart, which is designed to help students learn faster, study more efficiently, and retain more knowledge for greater success. In addition, Guided Examples provide students with narrated and animated, step-by-step walkthroughs of algorithmic versions of assigned exercises.