Student Solutions Manual for Business Statistics

Description

Teach students how statistics works — in the classroom and in the real world

Students see why the concepts they’re learning are important and how they’ll be used in everyday life.

• Current business examples are used throughout to grab and keep students’ interest. Many examples have been updated with more timely topics and data sets that relate to current business systems, technologies, and applications.
• Your Turn boxes follow the examples and give students a chance to practice a problem right after they’ve learned about it. Answers appear at the end of the chapters so students can check their work.
• Detailed end-of-chapter problems vary in difficulty level and type and provide instructors with flexibility.
• Focus on Analytics discusses business analytics examples and applications, so students can achieve competitiveness in their careers.

 

Coverage includes the most current thinking, practices, and software in the field

• Coverage of important topics, include:
• Data sets and databases, which explain definitions and show examples and tables (Chapter 1).
• How to create histograms using Excel charts, and Sparklines with definitions and steps (Chapter 2).
• How to use short-cut formulas to find the sample variance and standard deviation in Excel as well as demonstration of Excel to draw box-and-whisker plots (Chapter 3).
• How to create contingency tables with probabilities in Excel by using pivot table. More tables and explanations have been added to simplify the logic and process of deriving Bayes theorem (Chapter 4).
• How to find the mean of a discrete probability distribution in Excel (Chapter 5).
• How to use Excel to perform hypothesis tests for the mean when σ is known (Chapter 9).
• How to use Excel to determine the p-value (Chapters 12 and 13).
• Technology coverage to Microsoft Excel® 2016, including (online) instructions and figures, so instructors can successfully demonstrate the use of technology in business statistics. The 3rd Edition also focuses more on Excel’s Data Analysis ToolPak, which covers most functionalities needed in this course.
• Excel Projects call out certain topics in the text, from Describing and Calculating Data to Hypothesis Testing to Linear Regression, and point students to Excel assignments in MyLab Business Statistics. These assignments allow students to apply statistical analysis using Excel native functions and Excel’s Data Analysis Add-in.

Also available as a Pearson eText or packaged with MyLab Business Statistics

Pearson eText is a simple-to-use, mobile-optimized, personalized reading experience that can be adopted on its own as the main course material. It lets students highlight and take notes all in one place, even when offline. Learn more about Pearson eText.

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. For example, new Excel and StatCrunch Projects help students develop business decision-making skills. Learn more about MyLab Business Statistics.

• Pearson eText is a simple-to-use, mobile-optimized, personalized reading experience that can be adopted on its own as the main course material. It lets students highlight and take notes all in one place, even when offline.
• Using proven, field-tested technology, auto-graded Excel Projects let you seamlessly integrate Microsoft^® Excel^® content into your course without having to manually grade spreadsheets.
• 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.
• StatCrunch Projects provide opportunities for students to analyze big data, practice statistical thinking, and make data-informed decisions. Each project consists of a series of questions about a large data set to provide a deeper dive on business statistics topics.

Business statistics made accessible

Donnelly’s conversational writing style, friendly step-by-step approach, clearly presented concepts, and skillful use of business-focused examples give meaning to business statistics for today’s college students. From the moment they open the book, students get the sense of sitting down and having a conversation with the author.

• The engaging, straightforward tone pulls students into the material, without talking down to them, and helps them understand the concepts even before they realize they’re learning.
• The look and feel of the book is designed to be friendly and unintimidating.
• Key concepts — and why students need to know them — are effectively explained.
• Author comments in the margins call out quick tips and common mistakes to help clarify specific topics. Presented informally as written bubbles, they’re analogous to side comments instructors would make to students during a lecture to help them understand the material.
• Highlighted text ensures that students take notice of important points.

 

Teach students how statistics works — in the classroom and in the real world

Students see why the concepts they’re learning are important and how they’ll be used in everyday life.

• Learning Objectives open every chapter and help students guide their learning efforts.
• The “Learn It, Do It, Check It” cycle lets students learn by reading an example, work in a similar problem on their own, and then check their answer to confirm they understand.
• Updated – Current business examples are used throughout to grab and keep students’ interest. Many examples have been updated with more timely topics and data sets that relate to current business systems, technologies, and applications.
• A step-by-step approach to complicated problems breaks down the tougher topics and shows students the steps involved in small, bite-size portions of information. As a result, students have a consistent road map to follow when deciding how to proceed with a specific technique.
• Updated – Your Turn boxes follow the examples and give students a chance to practice a problem right after they’ve learned about it. Answers appear at the end of the chapters so students can check their work.
• Updated – Detailed end-of-chapter problems vary in difficulty level and type and provide instructors with flexibility.
• Statistics in Practice boxes use pertinent examples to grab students’ attention, clarify concepts, and show how statistics is used in today’s business environment.
• New – Focus on Analytics discusses business analytics examples and applications, so students can achieve competitiveness in their careers.
• Equations sections provide useful summaries of formulas.

 

Coverage includes the most current thinking, practices, and software in the field

• New and Updated – Coverage of important topics, include:
• Data sets and databases, which explain definitions and show examples and tables (Chapter 1).
• How to create histograms using Excel charts, and Sparklines with definitions and steps (Chapter 2).
• How to use short-cut formulas to find the sample variance and standard deviation in Excel as well as demonstration of Excel to draw box-and-whisker plots (Chapter 3).
• How to create contingency tables with probabilities in Excel by using pivot table. More tables and explanations have been added to simplify the logic and process of deriving Bayes theorem (Chapter 4).
• How to find the mean of a discrete probability distribution in Excel (Chapter 5).
• How to use Excel to perform hypothesis tests for the mean when σ is known (Chapter 9).
• How to use Excel to determine the p-value (Chapters 12 and 13).
• Updated – Technology coverage to Microsoft Excel® 2016, including (online) instructions and figures, so instructors can successfully demonstrate the use of technology in business statistics. The 3rd Edition also focuses more on Excel’s Data Analysis ToolPak, which covers most functionalities needed in this course.
• New – Excel Projects call out certain topics in the text, from Describing and Calculating Data to Hypothesis Testing to Linear Regression, and point students to Excel assignments in MyLab Business Statistics. These assignments allow students to apply statistical analysis using Excel native functions and Excel’s Data Analysis Add-in.

 

• 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.
• Pearson eText is a simple-to-use, mobile-optimized, personalized reading experience that can be adopted on its own as the main course material. It lets students highlight and take notes all in one place, even when offline.
• 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.
• Question Help consists of homework and practice questions to give students unlimited opportunities to master concepts. Learning aids walk students through the problem — giving them assistance when they need it most.
• The Study Plan gives students personalized recommendations, practice opportunities, and learning aids to help them stay on track.
• The Getting Ready for Statistics Library contains more than 450 exercises to ensure students have mastered the needed developmental math topics before beginning their statistics course. These are key for students who may need extra prerequisite support and can be added to any assignment.
• 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.
• New – Using proven, field-tested technology, auto-graded Excel Projects let you seamlessly integrate Microsoft^® Excel^® content into your course without having to manually grade spreadsheets.
• 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.
• New – StatCrunch Projects provide opportunities for students to analyze big data, practice statistical thinking, and make data-informed decisions. Each project consists of a series of questions about a large data set to provide a deeper dive on business statistics topics.
• Improve student results: When you teach with MyLab, student performance often improves. That’s why instructors have chosen MyLab for over 15 years, touching the lives of over 50 million students.

 

Robert (Bob) A. Donnelly, Jr. was a professor at Goldey-Beacom College in Wilmington, Delaware, with more than 25 years of teaching experience. He taught classes in statistics, operations management, spreadsheet modeling and project management at both the undergraduate and graduate level. Bob earned an undergraduate degree in chemical engineering from the University of Delaware, after which he worked for several years as an engineer with the Diamond Shamrock Corporation in a chlorine plant. Despite success in this field, Bob felt drawn to pursue a career in education. It was his desire to teach that took him back to school to earn his MBA and PhD in Operations Research, also from the University of Delaware. Bob also teaches in the MBA program at the International School of Management in Paris, France. He thoroughly enjoys discussing research methods and business statistics with both his French and American students.

 

Bob’s working experience gathered prior to his teaching career has provided him with many opportunities to incorporate real-life examples into classroom learning. His students appreciate his knowledge of the business world as well as his mastery of the course subject matter. Many former students seek Bob’s assistance in work-related issues that deal with his expertise. Typical student comments focus on his genuine concern for their welfare and his desire to help them succeed in reaching their goals.

 

ABOUT THE SPECIAL CONTRIBUTORS:

 

Serina Al Haddad, PhD, is a visiting assistant professor in the business department at Rollins College, where she teaches classes in business statistics. She taught classes in business statistics and analytics at Stetson University for three years and received the “Outstanding Teacher of the Year” Award in 2017. Serina also taught undergraduate and graduate classes in statistics and decision analysis at the University of Central Florida (UCF). She completed her doctorate from UCF in industrial engineering and management systems. She has over 14 years of experience working in both academia and industry. Serina held multiple positions in statistical quality control, customer relationship management, institutional development, and business process reengineering. She is a freelance consultant and trainer. Serina is one of the main authors of Excel Grader projects in Pearson MyLab Statistics. She has worked with many organizations including State University of New York and other USAID programs. Her research interests include statistics, business analytics, innovation, and organizational development. Serina is a member of the Institute of Industrial and Systems Engineering (IISE). She served as president of the IISE Student Chapter at her undergraduate university, for which she was a founding member.

 

Stefan Ruediger, PhD, is a clinical associate professor in the economics department in the W.P. Carey School of Business at Arizona State University, where he teaches classes in business statistics, managerial economics, and principles of macroeconomics. He taught classes in economics at the University of Wisconsin Stevens Point from 2008-2013 and received the School of Business and Economics Teaching Excellence Award in 2012. Stefan also taught undergraduate classes in economics at the University of Wisconsin Parkside and at the University of Wisconsin Milwaukee. He completed his doctorate from UWM. He has over 15 years of experience working in academia. His research is focused on Economic and Statistics Education, Economic Development, and Financial Economics. He has several publications in these areas and won awards for his research. Stefan has worked in collaboration with colleagues from ASU on developing new adaptive courseware tools, in-class instructional materials, instructional videos, and teaching modes to improve student success, student retention rates, and decrease withdrawal rates at ASU. These projects have been supported by grants from the Gates Foundation and the APLU. In addition, Stefan was a track and field coach at UWM for 5 years and a member of the German Bobsledding national team for 4 years. His athletic background always provides

a good basis for fun conversations with students and is a source of great economics and statistics examples.