ISBN | Product | Product | Price CHF | Available | |
---|---|---|---|---|---|
Statistics for Managers Using Microsoft Excel, Global Edition |
9781292338248 Statistics for Managers Using Microsoft Excel, Global Edition |
97.60 |
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This title is a Pearson Global Edition. The Editorial team at Pearson has worked closely with educators around the world to include content which is especially relevant to students outside the United States.
For one-semester courses in Introduction to Business Statistics.
The gold standard in learning Microsoft Excel for business statistics
Statistics for Managers Using Microsoft® Excel®, 9th Edition, Global Edition helps students develop the knowledge of Excel needed in future careers. The authors present statistics in the context of specific business fields, and now include a full chapter on business analytics. Guided by principles set forth by ASA’s Guidelines for Assessment and Instruction (GAISE) reports and the authors’ diverse teaching experiences, the text continues to innovate and improve the way this course is taught to students. Current data throughout gives students valuable practice analyzing the types of data they will see in their professions, and the authors’ friendly writing style includes tips and learning aids throughout.
The book also integrates PHStat, a statistical add-in that bolsters the functions of Excel. Extensive instructor and student resources are provided, including two online-only chapters, as well as the Digital Cases referenced in the text.
Pearson MyLab Statistics is not included. Students, if Pearson MyLab Statistics is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN. Pearson MyLab Statistics should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.
Student-focused learning aids
· An integrated five-step approach makes it easier for students to follow the progression of applying statistics: Define, Collect, Organize, Visualize, Analyze.
· First Things First sets the context for explaining what statistics is (not what students may think), while ensuring that they understand why learning business statistics is important today. This chapter is especially helpful for instructors using course management tools, including hybrid or online courses; this chapter is designed for distribution before the first class begins.
· REVISED - Tabular summaries guide readers to reaching conclusions and making decisions based on statistical information. Found in Chapters 10 through 13, this change not only adds clarity to the purpose of the statistical method being discussed but better illustrates the role of statistics in business decision-making processes.
· Student Tips in the margin reinforce hard-to-master concepts and provide quick study tips for mastering important details.
· LearnMore references reinforce important points and direct students to additional learning resources.
· Additional self-study opportunities are provided in an Appendix that offers answers to the “Self-Test” problems and most of the even-numbered problems in the book.
Focus on data interpretation and application
· Analyzing data with a focus on software results: Using software is essential to learning statistics. Software should model business best practices and be integrated into the statistical learning process. Reusable templates and model solutions are emphasized over building unaudited solutions from scratch that may contain errors. Using preconstructed and previously validated solutions not only models best practice but reflects regulatory requirements that businesses face today. This text emphasizes data analysis through interpretation of the results from Microsoft® Excel®:
o Excel content includes end-of-chapter Excel Guides; in-depth Excel step-by-step instructions; Excel Guide workbooks; PHStat, a statistics add-in system for Excel; and multiple appendices devoted to Excel.
o Software instruction sets are complete and contain known starting points. Vague instructions that present statements such as “Use command X” that presume students can figure out how to “get to” command X are distracting to learning. Instruction sets are provided that have a known starting point, typically in the form of “open to a specific worksheet in a specific workbook.”
o NEW - Tableau Guides in each chapter explain how to use Tableau Public, the data visualization software, as a complement to Microsoft Excel for visualizing data. The text offers Tableau Public results for selected methods in which Tableau can enhance or complement Excel results.
· REVISED - Using Statistics business scenarios begin each chapter. Scenarios are then used throughout the chapter to provide an applied context for the concepts, to bring students from knowing to applying. In the 9th Edition, Global Edition, seven chapters offer new or revised case scenarios.
o Help students see the relevance of statistics to their own careers by using examples from the functional areas that may become their areas of specialization. Every statistical method is discussed using an example from a functional area, such as accounting, finance, management, or marketing, and explaining the application of methods to specific business activities.
· NEW - Business Analytics chapter (Chapter 17) provides a complete introduction to the field of business analytics. The chapter defines terms and categories that introductory business statistics students may encounter in other courses or outside the classroom.
o NEW - Includes a new Consider This feature, “What’s My Major If I Want to Be a Data Miner?”
· Getting Ready to Analyze Data in the Future: The final chapter helps students understand how to make decisions about which statistical methods to use in real world problems. This capstone chapter brings the issues in First Things First scenarios full circle, and gives students the ability to apply business statistics to the real world.
· Consider This essays in every chapter reinforce important concepts, examine side issues, or answer typical student questions that arise while studying business statistics, such as “What is so ‘normal’ about the normal distribution?”
· End-of-chapter cases include a business case that continues through most chapters. Several cases that reoccur throughout the book.
o Case Studies offer realistic business scenarios to apply fundamental statistical and analytical concepts.
o Digital Cases ask students to examine interactive PDF documents and sift through claims and information in order to discover the data most relevant to a business case scenario. Students determine whether the conclusions and claims are supported by the data, and in doing so, they learn how to identify common misuses of statistical information.
o The Instructor’s Solutions Manual provides instructional tips for using cases as well as solutions to the Digital Cases.
· Software integration and flexibility: Software instructions feature chapter examples and were personally written by the authors. With modularized Workbook, PHStat, and Analysis Toolbook instructions where applicable, both instructors and students can switch among these instruction sets as they use this book with no loss of statistical learning.
Pearson MyLab Statistics is not included. Students, if Pearson MyLab Statistics is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN. Pearson MyLab Statistics should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.
Teach your course your way
· All data sets are available to download in the Pearson MyLab Statistics course or via the Pearson Math and Statistics Resource Site. These are available in Excel, JMP, and Minitab formats and contain the data used in chapter examples or named in problems and end-of-chapter cases.
· Technology-specific video tutorials and study cards provide students with support no matter which statistical software they use. The videos address how to use StatCrunch, Excel, Excel with PHStat, Excel with XLStat Minitab, R, and TI 83/84 calculators to complete exercises. There are also study cards available in Pearson MyLab Statistics for all listed software options, in addition to JMP.
· Learning Catalytics™ is a student response tool that uses students’ smartphones, tablets, or laptops to engage them in more interactive tasks and thinking. It helps to foster student engagement and peer-to-peer learning, generate class discussion, and guide lectures with real-time analytics.
Empower each learner
· NEW - Pearson eText is a simple-to-use, mobile-optimized, personalized reading experience available within MyLab.
· 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.
· Getting Ready for Statistics Questions: This question library contains more than 450 exercises that cover the relevant algebraic topics for a given section. These can be made available to students for extra practice or assigned as a prerequisite to other assignments.
· 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.
Deliver trusted content
· NEW - Excel Grader Projects: Excel Projects in Pearson MyLab Statistics allow students to analyze data using actual Microsoft Excel software. Each Excel project focuses on a key concept in the business statistics course and asks students to answer questions about a data set provided in Excel. Excel project questions are auto-graded and provide immediate feedback so students can identify any conceptual or procedural mistakes made in the problem-solving process. 23 separate statistical topics are covered.
· StatCrunch: This powerful, web-based statistical software is integrated into Pearson MyLab Statistics, so students can quickly and easily analyze any data set, including those from their text and Pearson MyLab Statistics exercises. In addition, Pearson MyLab Statistics includes access to www.StatCrunch.com, a web-based community where users can access tens of thousands of shared data sets, create and conduct online surveys, pull data from almost any web page, and perform complex analyses using the powerful statistical software.
· StatCrunch Reports get students hands-on with statistical procedures by guiding them through real data analysis in StatCrunch. When results are generated with just a few clicks, students can spend more time interpreting and communicating results. StatCrunch Reports are integrated into the text and are now accompanied by assignable questions in Pearson MyLab Statistics.
· StatCrunch Projects in Pearson MyLab Statistics provide opportunities for students to explore data beyond the classroom. In each project, students analyze a large data set in StatCrunch and answer corresponding, assignable questions for immediate feedback. StatCrunch Projects span the entire curriculum or focus on certain key concepts. Questions from each project can also be assigned individually.
· Conceptual Question Library: A library of 1000 conceptual questions in the Assignment Manager requires students to apply their statistical understanding.
· StatTalk Videos: Hosted by fun-loving statistician Andrew Vickers, this video series demonstrates important statistical concepts through interesting stories and real-life events. Videos include assessment questions and an instructor’s guide.
· New or revised Using Statistics case scenarios in seven chapters of the 9th Edition, Global Edition. These business scenarios begin each chapter, showing how statistics is used in accounting, finance, information systems, management, or marketing. Scenarios are then used throughout the chapter to provide an applied context for the concepts, to bring students from knowing to applying.
· New Tableau Guides in each chapter explain how to use the data visualization software Tableau Public as a complement to Microsoft® Excel® for visualizing data. The text offers Tableau Public results for selected methods in which Tableau can enhance or complement Excel results.
· A new Business Analytics chapter (Chapter 17) provides a complete introduction to the field of business analytics. The chapter defines terms and categories that introductory business statistics students may encounter in other courses or outside the classroom.
o Includes a new Consider This feature, “What’s My Major If I Want to Be a Data Miner?”
· Exercises have been reviewed, updated, and replaced in this edition.
· Tabular summaries now guide readers to reaching conclusions and making decisions based on statistical information. Found in Chapters 10 through 13, this change not only adds clarity to the purpose of the statistical method being discussed but better illustrates the role of statistics in business decision-making processes.
Pearson MyLab Statistics is not included. Students, if Pearson MyLab Statistics is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN. Pearson MyLab Statistics should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.
· Pearson eText is a simple-to-use, mobile-optimized, personalized reading experience available within MyLab.
· Excel Grader Projects: Excel Projects in MyLab™ Statistics allow students to analyze data using actual Microsoft Excel spreadsheet software. Each Excel project focuses on a key concept in the business statistics course and asks students to answer questions about a data set provided in Excel. Excel project questions are auto-graded and provide immediate feedback so students can identify any conceptual or procedural mistakes made in the problem-solving process. 23 separate statistical topics are covered.
First Things First
FTF.1 Think Differently About Statistics
FTF.2 Business Analytics: The Changing Face of Statistics
FTF.3 Starting Point for Learning Statistics
FTF.4 Starting Point for Using Software
FTF.5 Starting Point for Using Microsoft Excel
1. Defining and Collecting Data
1.1 Defining Variables
1.2 Collecting Data
1.3 Types of Sampling Methods
1.4 Data Cleaning
1.5 Other Data Preprocessing Tasks
1.6 Types of Survey Errors
2. Organizing and Visualizing Variables
2.1 Organizing Categorical Variables
2.2 Organizing Numerical Variables
2.3 Visualizing Categorical Variables
2.4 Visualizing Numerical Variables
2.5 Visualizing Two Numerical Variables
2.6 Organizing a Mix of Variables
2.7 Visualizing a Mix of Variables
2.8 Filtering and Querying Data 73
2.9 Pitfalls in Organizing and Visualizing Variables
3. Numerical Descriptive Measures
3.1 Measures of Central Tendency
3.2 Measures of Variation and Shape
3.3 Exploring Numerical Variables
3.4 Numerical Descriptive Measures for a Population
3.5 The Covariance and the Coefficient of Correlation
3.6 Descriptive Statistics: Pitfalls and Ethical Issues
4. Basic Probability
4.1 Basic Probability Concepts
4.2 Conditional Probability
4.3 Ethical Issues and Probability
4.4 Bayes’ Theorem
4.5 Counting Rules
5. Discrete Probability Distributions
5.1 The Probability Distribution for a Discrete Variable
5.2 Binomial Distribution
5.3 Poisson Distribution
5.4 Covariance of a Probability Distribution and Its Application in Finance
5.5 Hypergeometric Distribution
6. The Normal Distribution and Other Continuous Distributions
6.1 Continuous Probability Distributions
6.2 The Normal Distribution
6.3 Evaluating Normality
6.4 The Uniform Distribution
6.5 The Exponential Distribution
6.6 The Normal Approximation to the Binomial Distribution
7. Sampling Distributions
7.1 Sampling Distributions
7.2 Sampling Distribution of the Mean
7.3 Sampling Distribution of the Proportion
7.4 Sampling from Finite Populations
8. Confidence Interval Estimation
8.1 Confidence Interval Estimate for the Mean (σ Known)
8.2 Confidence Interval Estimate for the Mean (σ Unknown)
8.3 Confidence Interval Estimate for the Proportion
8.4 Determining Sample Size
8.5 Confidence Interval Estimation and Ethical Issues
8.6 Application of Confidence Interval Estimation in Auditing
8.7 Estimation and Sample Size Determination for Finite Populations
8.8 Bootstrapping
9. Fundamentals of Hypothesis Testing: One-Sample Tests
9.1 Fundamentals of Hypothesis Testing
9.2 t Test of Hypothesis for the Mean (σ Unknown)
9.3 One-Tail Tests
9.4 Z Test of Hypothesis for the Proportion
9.5 Potential Hypothesis-Testing Pitfalls and Ethical Issues
9.6 Power of the Test
10. Two-Sample Tests
10.1 Comparing the Means of Two Independent Populations
10.2 Comparing the Means of Two Related Populations
10.3 Comparing the Proportions of Two Independent Populations
10.4 F Test for the Ratio of Two Variances
10.5 Effect Size
11. Analysis of Variance
11.1 One-Way ANOVA
11.2 Two-Way ANOVA
11.3 The Randomized Block Design
11.4 Fixed Effects, Random Effects, and Mixed Effects Models
12. Chi-Square and Nonparametric Tests
12.1 Chi-Square Test for the Difference Between Two Proportions
12.2 Chi-Square Test for Differences Among More Than Two Proportions
12.3 Chi-Square Test of Independence
12.4 Wilcoxon Rank Sum Test for Two Independent Populations
12.5 Kruskal-Wallis Rank Test for the One-Way ANOVA
12.6 McNemar Test for the Difference Between Two Proportions (Related Samples)
12.7 Chi-Square Test for the Variance or Standard Deviation
12.8 Wilcoxon Signed Ranks Test for Two Related Populations
13. Simple Linear Regression
13.1 Simple Linear Regression Models
13.2 Determining the Simple Linear Regression Equation
13.3 Measures of Variation
13.4 Assumptions of Regression
13.5 Residual Analysis
13.6 Measuring Autocorrelation: The Durbin-Watson Statistic
13.7 Inferences About the Slope and Correlation Coefficient
13.8 Estimation of Mean Values and Prediction of Individual Values
13.9 Potential Pitfalls in Regression
14. Introduction to Multiple Regression
14.1 Developing a Multiple Regression Model
14.2 Evaluating Multiple Regression Models
14.3 Multiple Regression Residual Analysis
14.4 Inferences About the Population Regression Coefficients
14.5 Testing Portions of the Multiple Regression Model
14.6 Using Dummy Variables and Interaction Terms
14.7 Logistic Regression
14.8 Cross-Validation
15. Multiple Regression Model Building
15.1 The Quadratic Regression Model
15.2 Using Transformations in Regression Models
15.3 Collinearity
15.4 Model Building
15.5 Pitfalls in Multiple Regression and Ethical Issues
16. Time-Series Forecasting
16.1 Time-Series Component Factors
16.2 Smoothing an Annual Time Series
16.3 Least-Squares Trend Fitting and Forecasting
16.4 Autoregressive Modeling for Trend Fitting and Forecasting
16.5 Choosing an Appropriate Forecasting Model
16.6 Time-Series Forecasting of Seasonal Data
16.7 Index Numbers
17. Business Analytics
17.1 Business Analytics Overview
17.2 Descriptive Analytics
17.3 Decision Trees
17.4 Clustering
17.5 Association Analysis
17.6 Text Analytics
17.7 Prescriptive Analytics
18. Getting Ready to Analyze Data in the Future
18.1 Analyzing Numerical Variables
18.2 Analyzing Categorical Variables
19. Statistical Applications in Quality Management (online)
19.1 The Theory of Control Charts
19.2 Control Chart for the Proportion: The p Chart
19.3 The Red Bead Experiment: Understanding Process Variability
19.4 Control Chart for an Area of Opportunity: The c Chart
19.5 Control Charts for the Range and the Mean
19.6 Process Capability
19.7 Total Quality Management
19.8 Six Sigma
20. Decision Making (online)
20.1 Payoff Tables and Decision Trees
20.2 Criteria for Decision Making
20.3 Decision Making with Sample Information
20.4 Utility
Appendices
Indices
Credits