Using Statistics for Better Business Decisions

  • 3h 30m
  • Bert G. Wachsmuth, Justin Bateh
  • Business Expert Press
  • 2016

More and more organizations around the globe are expecting that professionals will make data-driven decisions. Employees, team leaders, managers, and executives that can think quantitatively should be in high demand. The goal of this book is to increase ability to identify a problem, collect data, organize, and analyze data that will help aid in making more effective decisions.

This book will provide you with a solid foundation for thinking quantitatively within your company. To help facilitate this objective, this book follows two fictitious companies that encounter a series of business problems, while demonstrating how managers would use the concepts in the book to solve these problems and determine the next course of action. This book is for beginners and does not require prior statistical training. All computations will be completed using Microsoft Excel.

About the Authors

Dr. Justin Bateh is a professor in the School of Business & Professional Studies at Florida State College at Jacksonville, where he teaches management, operations, and statistics courses. He received a doctorate in business administration from Walden University. Following his doctoral studies he pursued post-graduate specializations from Penn State University in applied statistics and from the University of Arkansas in operations management.

Dr. Bert G. Wachsmuth, associate professor of mathematics and computer Science at Seton Hall University, received his PhD from Indiana University, where he worked on problems related to the Monge Ampère Equation in several complex variables. In addition to pursuing a rigorous research program, Dr. Wachsmuth is an avid programmer and he is currently interested - aside from mathematics - in robotics, small device programming, and technology applications in teaching and learning.

In this Book

  • Statistics and Statistical Software
  • Data Visualization
  • Numerical Data Summary
  • Probability Theory
  • Estimation
  • Hypothesis Testing
  • Association Between Categorical Variables
  • Linear Regression
  • Analysis of Variance