Student Solutions Manual for Basic Business Statistics

Student Solutions Manual for Basic Business Statistics

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Helps students understand the role of statistics in their future careers

  • New – This edition contains a new Business Analytics Chapter that makes extensive use of JMP and Minitab to illustrate predictive analytics for prediction, classification, clustering, and association, as well as explaining what text analytics does and how descriptive and prescriptive analytics relate to predictive analytics.
  • Updated Examples and Using Statistics business scenarios are drawn from all functional areas of business, helping students see how the concepts they’re learning apply to their future careers and providing an applied context for learning.
  • Project-Detailed Case Studies are included in numerous chapters. The Managing Ashland MultiComm Services continuing case, a team project related to bond funds, and undergraduate and graduate student surveys feature at the end of most chapters, helping to integrate learning across the chapters.
  • Digital Cases let students examine interactive PDFs to sift through various claims and information, discover the conclusions and claims supported by the data, and identify common misuses of statistical information.

Gives students a framework to learn and understand statistical concepts 

  • Updated – This text emphasizes data analysis and the interpretation of the results of a statistical method, rather than focusing on the mathematics of a method. The 14th Edition includes JMP results, supplementing the Excel and Minitab results from previous editions.
  • Visual Explorations allow students to interactively explore important statistical concepts in descriptive statistics, the normal distribution, sampling distributions, and regression analysis by using an Excel® add-in workbook and unique Excel integration.
  • New – Chapters 9 through 15 now include Tabular Summaries that state hypothesis test and regression example results, along with the conclusions that those results support.
  • Features like Consider This essays and LearnMore bubbles provide greater insight into the material and raise important issues about the application of statistical knowledge.

Enhances learning with flexible online features and software integration 

  • Integrates Excel with Visual Explorations that demonstrate basic concepts, and designed and implemented PHStat, the Pearson statistical add-in for Excel that places the focus on statistical learning.
  • An extensive online library of separate topics, sections, and two full chapters allows instructors to tailor these materials to meet their curricular needs, and provides opportunities for additional learning.
  • New – A First Things First Chapter, available as a complimentary online download, allows students to get a head start on learning and uses real-world examples to illustrate how developments, such as the increasing use of business analytics and “big data,” have made knowing and understanding statistics even more important.
  • Updated New JMP Guides and updated Excel and Minitab Guides provide detailed, hands-on instructions for using the most recent editions of those programs in business decision making, with templates and applications designed to minimize the frustration of using the software and maximize statistical learning. The modularized nature of the software allows instructors and students to switch between applications as they use the book.

Also available with MyLab Business Statistics

MyLab™ is the teaching and learning platform that empowers you to reach every student. By combining trusted author content with digital tools and a flexible platform, MyLab personalizes the learning experience and improves results for each student. Learn more about MyLab Business Statistics.

Reach every student with MyLab

  • Deliver trusted content: You deserve teaching materials that meet your own high standards for your course. That’s why we partner with highly respected authors to develop interactive content and course-specific resources that you can trust — and that keep your students engaged.
    • StatCrunch, a powerful, web-based statistical software, is integrated into MyLab, so students can quickly and easily analyze data sets from their text and exercises.
    • Diverse Question Libraries: Build homework assignments, quizzes, and tests to support your course learning outcomes. From Getting Ready (GR) questions to the Conceptual Question Library (CQL), we have your assessment needs covered from the mechanics to the critical understanding of Statistics. The exercise libraries include technology-led instruction, including new Excel-based exercises, and learning aids to reinforce your students’ success.
  • Empower each learner: Each student learns at a different pace. Personalized learning pinpoints the precise areas where each student needs practice, giving all students the support they need — when and where they need it — to be successful.
    • Tutorials and Study Cards for Statistical Software: Tutorials provide brief video walkthroughs and step-by-step instructional study cards on common statistical procedures such as confidence interval estimation, ANOVA, regression, and hypothesis testing. Tutorials and study cards are supplied for Excel 2013 and 2016, Excel with PHStat, JMP, and Minitab.
    • The Study Plan gives students personalized recommendations, practice opportunities, and learning aids to help them stay on track.
  • Teach your course your way: Your course is unique. So whether you’d like to build your own assignments, teach multiple sections, or set prerequisites, MyLab gives you the flexibility to easily create your course to fit your needs.
    • The Gradebook offers an easy way for you and your students to see their performance in your course.
  • Improve student results: When you teach with MyLab, student performance improves. That’s why instructors have chosen MyLab for over 15 years, touching the lives of over 50 million students. 
Check out the preface for a complete list of features and what’s new in this edition.

Mark L. Berenson is Professor of Information Management and Business Analytics at Montclair State University and Professor Emeritus of Information Systems and Statistics at Baruch College. He currently teaches graduate and undergraduate courses in statistics and operations management in the School of Business, and an undergraduate course in international justice and human rights that he co-developed in the College of Humanities and Social Sciences.

Berenson received a BA in economic statistics and an MBA in business statistics from City College of New York and a PhD in business from the City University of New York. Berenson’s research has been published in Decision Sciences Journal of Innovative Education, Review of Business Research, The American Statistician, Communications in Statistics, Psychometrika, Educational and Psychological Measurement, Journal of Management Sciences and Applied Cybernetics, Research Quarterly, Stats Magazine, The New York Statistician, Journal of Health Administration Education, Journal of Behavioral Medicine, and Journal of Surgical Oncology. His invited articles have appeared in The Encyclopedia of Measurement & Statistics and Encyclopedia of Statistical Sciences. He has coauthored numerous statistics texts published by Pearson. Over the years, Berenson has received several awards for teaching and for innovative contributions to statistics education. In 2005, he was the first recipient of the Catherine A. Becker Service for Educational Excellence Award at Montclair State University and, in 2012, he was the recipient of the Khubani/Telebrands Faculty Research Fellowship in the School of Business.

David Levine, Professor Emeritus of Statistics and CIS at Baruch College, CUNY, has been a nationally recognized innovator in statistics education for more than three decades. Levine has coauthored 14 books, including several business statistics textbooks; textbooks and professional titles that explain and explore quality management and the Six Sigma approach; and, with David Stephan, a trade paperback that explains statistical concepts to a general audience. Levine has presented or chaired numerous sessions about business education at leading conferences conducted by the Decision Sciences Institute (DSI) and the American Statistical Association, and he and his coauthors have been active participants in the annual DSI Data, Analytics, and Statistics Instruction (DASI) mini-conference. During his many years teaching at Baruch College, Levine was recognized for his contributions to teaching and curriculum development with the College’s highest distinguished teaching honor. He earned BBA and MBA degrees from CCNY, and a PhD in industrial engineering and operations research from New York University.

 

As Associate Professor of Business Systems and Analytics at La Salle University, Kathryn Szabat has transformed several business school majors into one interdisciplinary major that better supports careers in new and emerging disciplines of data analysis, including analytics. Szabat strives to inspire, stimulate, challenge, and motivate students through innovation and curricular enhancements, and shares her coauthors’ commitment to teaching excellence and the continual improvement of statistics presentations. Beyond the classroom, she has provided statistical advice to numerous business, non-business, and academic communities, with particular interest in the areas of education, medicine, and nonprofit capacity building. Her research activities have led to journal publications, chapters in scholarly books, and conference presentations. Szabat is a member of the American Statistical Association (ASA), DSI, Institute for Operation Research and Management Sciences (INFORMS), and DSI DASI. She received a BS from SUNY-Albany, an MS in statistics from the Wharton School of the University of Pennsylvania, and a PhD degree in statistics, with a cognate in operations research, from the Wharton School of the University of Pennsylvania.

Advances in computing have always shaped David Stephan’s professional life. As an undergraduate, he helped professors use statistics software that was considered advanced, even though it could compute only several things discussed in Chapter 3, thereby gaining an early appreciation for the benefits of using software to solve problems (and perhaps positively influencing his grades). An early advocate of using computers to support instruction, he developed a prototype of a mainframe-based system that anticipated features found today in Pearson’s MathXL, and served as special assistant for computing to the Dean and Provost at Baruch College. In his many years teaching at Baruch, Stephan implemented the first computer-based classroom, helped redevelop the CIS curriculum, and as part of a FIPSE project team, designed and implemented a multimedia learning environment. He was also nominated for teaching honors. Stephan has presented at SEDSI and DSI DASI (formerly MSMESB) mini-conferences, sometimes with his coauthors. Stephan earned a BA from Franklin & Marshall College and an MS from Baruch College, CUNY, and completed the instructional technology graduate program at Teachers College, Columbia University.

  • First Things First (online)
  1. Defining and Collecting Data
  2. Organizing and Visualizing Variables
  3. Numerical Descriptive Measures
  4. Basic Probability
  5. Discrete Probability Distributions
  6. The Normal Distribution and Other Continuous Distributions
  7. Sampling Distributions
  8. Confidence Interval Estimation
  9. Fundamentals of Hypothesis Testing: One-Sample Tests
  10. Two-Sample Tests
  11. Analysis of Variance
  12. Chi-Square and Nonparametric Tests
  13. Simple Linear Regression
  14. Introduction to Multiple Regression
  15. Multiple Regression Model Building
  16. Time-Series Forecasting
  17. Business Analytics
  18. Getting Ready to Analyze Data in the Future
  19. Statistical Applications in Quality Management (online)
  20. Decision Making (online)

Helps students understand the role of statistics in their future careers

  • This edition contains a new Business Analytics Chapter that makes extensive use of JMP and Minitab to illustrate predictive analytics for prediction, classification, clustering, and association, as well as explaining what text analytics does and how descriptive and prescriptive analytics relate to predictive analytics.
  • Examples and Using Statistics business scenarios are drawn from all functional areas of business, helping students see how the concepts they’re learning apply to their future careers and providing an applied context for learning.

Gives students a framework to learn and understand statistical concepts 

  • This text emphasizes data analysis and the interpretation of the results of a statistical method, rather than focusing on the mathematics of a method. The 14th Edition includes JMP results, supplementing the Excel and Minitab results from previous editions.
  • Chapters 9 through 15 now include Tabular Summaries that state hypothesis test and regression example results, along with the conclusions that those results support.

Enhances learning with flexible online features and software integration 

  • A First Things First Chapter, available as a complimentary online download, allows students to get a head start on learning and uses real-world examples to illustrate how developments, such as the increasing use of business analytics and “big data,” have made knowing and understanding statistics even more important. 
  • New JMP Guides and updated Excel and Minitab Guides provide detailed, hands-on instructions for using the most recent editions of those programs in business decision making, with templates and applications designed to minimize the frustration of using the software and maximize statistical learning. The modularized nature of the software allows instructors and students to switch between applications as they use the book.

Check out the preface for a complete list of features and what’s new in this edition.

Additional information

Dimensions 1.15 × 8.50 × 10.80 in
Imprint

Format

ISBN-13

ISBN-10

Author

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Subjects

statistics, mathematics, higher education, business statistics