Product details

  • Publisher: Wiley; 3rd Canadian Edition (May  , 2020)
  • Language: English
  • ISBN-13: 978-1119577584

Business Statistics For Contemporary Decision Making 3rd Canadian Edition Black Test Bank


Business Statistics continues the tradition of presenting and explaining the wonders of business statistics through a clear, complete, student-friendly pedagogy. In this third Canadian edition, authors Ken Black, Ignacio Castillo and Tiffany Bailey use 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. 
Business Statistics For Contemporary Decision Making 3rd Canadian Edition Black
  1. Introduction to Statistics 
  2. 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
  • NEW Business Analytics Coverage:  Helping the student understand business analytics and the role that business statistics plays in it, the third Canadian edition has infused the language of business analytics along with its definitions, approaches, and explanations throughout this course. 
  • NEW Big Data Case:  Using data that is available for hospitals in North America, this running case provides students the opportunity to use variables, samples and data from a large database to complete several end of case activities. 
  • NEW Visualizing Time-Series Data Section:  helps students use historical data with measures taken over time to predict what might happen in the future. 
Business Statistics For Contemporary Decision Making 3rd Canadian Edition Black
  • 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. 
  • Additional Databases: Databases representing several industries including agriculture, energy, environmental, finance, stocks and more provide additional opportunities for students to apply the statistics presented in each chapter. 
  • Key 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. 

About the Authors

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.

Ignacio Castillo is a professor of operations and decision sciences at the Lazaridis School of Business & Economics, Wilfrid Laurier University. He holds a Ph.D. in industrial engineering from Texas A&M University, an M.S.E. in industrial engineering from Arizona State University, and a B.S. (magna cum laude) in applied sciences from Universidad San Francisco de Quito, Ecuador. His research and teaching interests include business statistics, facility location, facility layout and material handling systems, manufacturing and service operations and logistics, and sustainable and closed-loop supply chain management. Dr. Castillo is a former LASPAU Scholar and Glenn Carroll Teaching Fellow, has served as adjunct faculty at the University of Alberta and the University of Waterloo, and is a member of the Alpha Pi Mu Industrial Engineering Honor Society, The Honor Society of Phi Kappa Phi, and Pinnacle Honor Society.

Tiffany Bayley is an assistant professor of operations and decision sciences at the Lazaridis School of Business & Economics, Wilfrid Laurier University. She holds a Ph.D. and M.A.Sc in applied operations research from the University of Waterloo, and a B.A.Sc in industrial and manufacturing systems engineering from the University of Windsor. Her research and teaching interests include business analytics, optimization and decomposition approaches for production planning, healthcare, and supply chain management problems, and experiential learning design for operations management and business analytics pedagogy. Dr. Bayley received the Natural Sciences and Engineering Research Council of Canada (NSERC) Alexander Graham Bell Canada Graduate Scholarship and the NSERC Post Graduate Doctoral Scholarship. She is a member of the Canadian Operational Research Society (CORS) and Institute for Operations Research and the Management Sciences (INFORMS).

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