Description

Business Statistics: A Decision Making Approach provides students with an introduction to business statistics and to the analysis skills and techniques needed to make successful real-world business decisions.

Written for students of all mathematical skill levels, the authors present concepts in a systematic and ordered way, drawing from their own experience as educators and consultants. Rooted in the theme that data are the starting point, Business Statistics champions the need to use and understand different types of data and data sources to be effective decision makers.

This new edition integrates Microsoft Excel throughout as a way to work with statistical concepts and give students a resource that can be used in both their academic and professional careers.

Features

• Business Applications and decision-making emphasis. New applications are included and are highlighted in the text with special icons, making them easier for students to locate as they use the text.
• Quick Prep Links at the beginning of the chapter provide several ways to prepare for the topics discussed.
• Chapter Outcomes identify the benefits of completing the following chapter, linked to the corresponding main headings. The chapter outcomes are recalled throughout the text to remind students of the objectives.
• Excel Functions text boxes, located in the text margin next to chapter examples, provide the Excel function that students can use to complete a specific test or calculation.
• A step-by-step approach emphasises concise, ordered details to reinforce chapter material.
• How to Do It lists summarise major techniques and fundamental concepts. Textual examples give step-by-step details, allowing students to easily follow solution techniques. Students can apply the methodology from each example to solve other problems.
• Textual Examples throughout the text provide step-by-step details, enabling students to easily follow solution techniques. These examples add to the vast array of business applications to give students a competitive edge.
• Real-World Business Applications feature real companies, actual applications, rich data sets, all to help promote realistic decision making. These applications are motivational, thereby helping students understand the relevance of statistics. They are clearly indicated with special icons and cover areas from accounting and finance to supply chain management. This allows the authors to concentrate on addressing how students apply this statistical knowledge to decision-making.
• Chapter Cases give students the opportunity to apply statistical tools. Each case challenges students to define a problem, determine the appropriate tool to use, apply it, and then write a summary report.
• Special Review Sections provide a review of the key issues and statistical techniques. Highly effective flow diagrams help students decide which technique is appropriate for a given problem or exercise. They serve as a mini-decision support system that reduces the need for memorisation and encourages students to seek a deeper understanding and learning. Integrative questions and exercises ask students to demonstrate their comprehension of the topics covered.
• Problems and exercises feature an extensive range of exercises to test the student’s understanding of the text. These are broken down into three categories:
• Skill Development to expand upon statistical methods learned in the chapter.
• Business Applications involving realistic situations in which students apply decision-making techniques.
• Computer Software Exercises, often with associated data files, are solved using Excel, Minitab, or other statistical software.
• Computer Integration combines computer applications with textual examples and figures, always focusing on interpreting the output. The goal is to guide students in which tools to use, how to apply the tools, and how to analyse their results for making decisions.
• Microsoft Excel 2016 integration instructs students in how to use the Excel 2016 interface for statistical applications.

New to this Edition

· Textual Examples include many new business examples throughout the text provide step-by-step details, enabling students to follow solution techniques easily. These examples are provided in addition to the vast array of business applications to give students a real-world, competitive edge.

· More Excel 2016 Focus: This edition features Excel 2016 with screen captures used extensively throughout the text to illustrate how this highly regarded software is used as an aid to statistical analysis.

· Excel 2016 features are highlighted throughout the text, including Statistic Chart, which enables the quick construction of histograms, and box and whisker plots. Forecasting Sheet, a new data feature in Excel, allows for time series forecasting and is applied throughout this edition's forecasting chapter.

· Business Applications have been included to provide students with current examples showing how the statistical techniques introduced in the text are used by real companies. The new applications involve companies, products, and decision-making scenarios that are familiar to and help students understand the relevance of statistics.

· A Business Analytics chapter introduces students to basic business intelligence and business analytics concepts and tools. Students discover how to use Microsoft's Power BI tool to analyze large data sets. Coverage includes loading data files into Power BI, establishing links between large data files, creating new variables and measures, and creating dashboards and reports using the Power BI tool.

· Exercises and Data Files have been included throughout the text, and other exercises have been revised and updated. Many new data files have been added to correspond to the new Computer Software Exercises, and other data files have been updated with current data.

· Improved Notation: The notation associated with population and sample proportions has been revised and improved to be consistent with the general approach taken by most faculty who teach the course.

· Test Manual has been prepared with questions that correspond directly to this new edition.

MyLab^TM Statistics not included. Students, if MyLab is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyLab should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.

Empower any student to apply and interpret Statistics procedures, getting to statistical understanding faster

· Learning CatalyticsTM helps you generate class discussion, customize your lecture, and promote peer-to-peer learning with real-time analytics. As a student response tool, Learning Catalytics uses students’ smartphones, tablets, or laptops to engage them in more interactive tasks and thinking.

o Help your students develop critical thinking skills.

o Monitor responses to find out where your students are struggling.

o Rely on real-time data to adjust your teaching strategy.

o Automatically group students for discussion, teamwork, and peer-to-peer learning.

o Upload a full PowerPoint® deck for easy creation of slide questions.

o Team names are no longer case sensitive.

Support students as they learn to use statistical software, to save valuable class time and prepare them for their future careers--whatever they may be

· Tech-Specific Video Tutorials are short, topical videos that address how to use varying tech

Table of Contents

• The Where, Why, and How of Data Collection
• Graphs, Charts, and Tables–Describing Your Data
• Describing Data Using Numerical Measures
• Introduction to Probability
• Discrete Probability Distributions
• Introduction to Continuous Probability Distributions
• Introduction to Sampling Distributions
• Estimating Single Population Parameters
• Introduction to Hypothesis Testing
• Estimation and Hypothesis Testing for Two Population Parameters
• Hypothesis Tests and Estimation for Population Variances
• Analysis of Variance
• Goodness-of-Fit Tests and Contingency Analysis
• Introduction to Linear Regression and Correlation Analysis
• Multiple Regression Analysis and Model Building
• Analyzing and Forecasting Time-Series Data
• Introduction to Nonparametric Statistics
• Introducing Business Analytics