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For one-semester courses in Introduction to Business Statistics.
The gold standard in learning Microsoft Excelfor business
statistics Statistics for Managers Using Microsoft (R) Excel (R),
9th Edition, Global Edition helps students develop the knowledge of
Excel needed in future careers. The authors present statistics in
the context of specific business fields, and now include a full
chapter on business analytics. Guided by principles set forth by
ASA's Guidelines for Assessment and Instruction (GAISE) reports and
the authors' diverse teaching experiences, the text continues to
innovate and improve the way this course is taught to students.
Current data throughout gives students valuable practice analysing
the types of data they will see in their professions, and the
authors' friendly writing style includes tips and learning aids
throughout.
For one- or-two-semester courses in business statistics. Give
students the statistical foundation to hone their analysis skills
for real-world decisions Basic Business Statistics helps students
see the essential role that statistics will play in their future
careers by using examples drawn from all functional areas of
real-world business. Guided by principles set forth by ASA's
Guidelines for Assessment and Instruction (GAISE) reports and the
authors' diverse teaching experiences, the text continues to
innovate and improve the way this course is taught to students. The
14th Edition includes new and updated resources and tools to
enhance students' understanding, and provides the best framework
for learning statistical concepts.
For one-semester business statistics courses. A focus on using
statistical methods to analyse and interpret results to make
data-informed business decisions Statistics is essential for all
business majors, and Business Statistics: A First Course helps
students see the role statistics will play in their own careers by
providing examples drawn from all functional areas of business.
Guided by the principles set forth by major statistical and
business science associations (ASA and DSI), plus the authors'
diverse experiences, the 8th Edition, Global Edition, continues to
innovate and improve the way this course is taught to all students.
With new examples, case scenarios, and problems, the text continues
its tradition of focusing on the interpretation of results,
evaluation of assumptions, and discussion of next steps that lead
to data-informed decision making. The authors feel that this
approach, rather than a focus on manual calculations, better serves
students in their future careers. This brief offering, created to
fit the needs of a one-semester course, is part of the established
Berenson/Levine series.
Businesses are collecting massive amounts of data every day as a
way to better understand their processes, competition, and the
markets they serve. This data can be used to increase
organizational productivity and performance; however, is essential
that organizations collecting large data sets have the tools
available to them to fully understand the data they are collecting.
Organizational Productivity and Performance Measurements Using
Predictive Modeling and Analytics takes a critical look at methods
for enhancing an organization's operations and day-to-day
activities through the effective use of data. Focusing on a variety
of applications of predictive analytics within organizations of all
types, this critical publication is an essential resource for
business managers, data scientists, graduate-level students, and
researchers.
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