Business Statistics: For Contemporary Decision Making, 10th Edition

Book Cover

Business Statistics: For Contemporary Decision Making, 10th Edition

By Ken Black

Business Statistics continues the tradition of presenting and explaining the wonders of business statistics through a clear, complete, student-friendly pedagogy. In this 10th edition, author Ken Black uses current real-world data to equip students with the business analytics techniques and quantitative decision-making skills required to make smart decisions in today’s workplace.To improve the learning experience for all students, WileyPLUS includes a clear, customizable and mobile-friendly learning path packed with homework practice, Lecture and Applied Skills videos, visualization exercises, an e-book, Bloomberg videos and much more.

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Hear from our Authors

Data Analytics Module

NEW Data Analytics & Decision-Making Module prepares students for the changing workplace.

With the emergence of Data Analytics transforming the business environment, Wiley has partnered with business leaders in the Business-Higher Education Forum (BHEF) to identify the competencies graduates need to be successful in their careers. As a result, this module includes industry-validated content that prepares business statistics students for the changing workforce.

NEW Real-World Video Activities provide business context.

WileyPLUS now offers a set of graded analysis activities that pair cutting-edge business video content from Bloomberg with concepts from the Black text. This new resource provides students with an applied and engaging learning experience to supplement their business statistics course.

Engaging videos help increase comprehension.

Lecture and Applied Skills Videos – about 40 in total – feature author, Ken Black as he introduces key concepts to students in a way they can understand.

    What’s New

  • NEW Business Analytics Coverage: Helping the student understand business analytics and the role that business statistics plays in it, the 10th edition has infused the language of business analytics along with its definitions, approaches, and explanations throughout this course.
  • Decision Dilemmas: Each course section is introduced with a real-world business vignette that presents a dilemma and related managerial or statistical questions. Solutions to these questions require the use of techniques presented in the section. A Decision Dilemma Solved feature concludes each section, giving students the opportunity to answer and discuss each question presented at the beginning of the section.
  • Thinking Critically About Statistics in Business Today Exercises: Each course section features one or several of these exercises that give real-life examples of how the statistics presented in the section apply in the business world today.
  • EXPANDED Databases: Twenty databases representing several industries including banking, consumer spending, energy, environmental, finance, manufacturing, healthcare, market research, retailing, stocks and more provide additional opportunities for students to apply the statistics presented in each chapter.
  • NEW Big Data Case: Using data from the American Hospital Association, each chapter contains an activity asking students to perform several tasks using variables, samples, and data.
  • NEW Visualizing Time-Series Data Section: helps students use historical data with measures taken over time to predict what might happen in the future.
  • Ethical Considerations: This feature in each course section integrates the topic of ethics with applications of business statistics.
  • Tree Taxonomy Diagrams: These diagrams illustrate the connection between topics and techniques and the ability to see the big picture of inferential statistics.
  • Section Reorganization Options: This course was designed to allow for both one- and two-semester coverage.
  • 900+ Practice Problems: A treasury of practice problems are available in this course.

Ken Black

Ken Black is currently professor of decision sciences in the School of Business at the University of Houston–Clear Lake. Born in Cambridge, Massachusetts, and raised in Missouri, he earned a bachelor’s degree in mathematics from Graceland University, a master’s degree in math education from the University of Texas at El Paso, a Ph.D. in business administration (management science), and a Ph.D. in educational research from the University of North Texas.

Since joining the faculty of UHCL in 1979, Professor Black has taught all levels of statistics courses, business analytics, forecasting, management science, market research, and production/operations management. In 2014, he received the Outstanding Professor Alumni Award from University of Houston – Clear Lake. In 2005, he was awarded the President’s Distinguished Teaching Award for the university. He has published over 20 journal articles and 20 professional papers, as well as two textbooks: Business Statistics: An Introductory Course and Business Statistics for Contemporary Decision Making. Black has consulted for many different companies, including Aetna, the city of Houston, NYLCare, AT&T, Johnson Space Center, Southwest Information Resources, UTMB, and Doctors Hospital at Renaissance. Black is active in the quality movement and is a certified Master Black Belt in Lean Six Sigma. Ken Black and his wife, Carolyn, have two daughters, Caycee and Wendi, and a grandson, Antoine. His hobbies include playing the guitar, reading, and traveling.

  1. Introduction to Statistics and Business Analytics
  2. Visualizing the Data with Charts and Graphs
  3. Descriptive Statistics
  4. Probability
  5. Discrete Distributions
  6. Continuous Distributions
  7. Sampling and Sampling Distributions
  8. Statistical Inference: Estimation for Single Populations
  9. Statistical Inference: Hypothesis Testing for Single Populations
  10. Statistical Inferences About Two Populations
  11. Analysis of Variance and Design of Experiments
  12. Simple Regression Analysis and Correlation
  13. Multiple Regression Analysis
  14. Building Multiple Regression Models
  15. Time-Series Forecasting and Index Numbers
  16. Analysis of Categorical Data
  17. Nonparametric Statistics
  18. Statistical Quality Control
  19. Decision Analysis

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