Worksheets for Statistics

Description

Emphasis on making informed decisions

Mike Sullivan helps students connect statistical concepts with their everyday lives, teaching them to think critically and make informed decisions.

• Putting It Together features connect concepts from different chapters to show statistics as a whole, rather than a series of disconnected procedures. Putting It Together sections ask students to identify the correct approach to solving a problem, while Putting It Together problems integrated throughout the text help students to tie concepts together and see the entire statistical process. 
• Making an Informed Decision chapter openers pose a question, and then present the statistical concept necessary for prudent decision-making. This feature engages the reader in the statistical-thinking process and highlights the practicality of statistics.
• UPDATED – The Student Activity Workbook includes new activities to be used with students, as well as ideas for semester-long projects, including the use of StatCrunch. Accompanied by an instructor resource guide with suggestions for incorporating activities into the classroom, the workbook helps to actively engage students with the material.
• NEW – Author-specific applets made for this course can be used in the classroom or as part of a project featured in the Activity Workbook, asking students to manipulate data using technology to better understand concepts. New applet exercises in the MyLab encourage this exploration.
• Case Studies conclude each chapter, promoting active learning and helping students apply their knowledge.
• StatCrunch is a powerful, web-¿based statistical software integrated into MyLab Statistics, so students can quickly and easily analyze any data set, including those from their text and MyLab Statistics exercises. StatCrunch 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 Projects in 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. 

Opportunities for self-assessment and prerequisite mastery

Throughout the course, features that enable students to check their understanding – or get up to speed on prerequisites in a corequisite course – are available to provide optimal support. 

• UPDATED –  Integrated Review in the MyLab course offers corequisite support – or can be used simply to get underprepared students up to speed. Based on the author’s own experience with corequisite courses, Integrated Review provides embedded and personalized review of prerequisite topics, selected by the author, within relevant chapters. In this revision, select topics have been added to provide further review. All assignments are premade and editable for instructors to assign.
• Premade, assignable Skills Check assignments check each student’s understanding of prerequisite skills needed to be successful in the following chapter. 
• For any skills gaps that are identified, a personalized review homework is populated. Students receive personalized practice on the topics they need to focus on – no more, no less.
• For any topics a student may have gaps on, a suite of resources support student learning. Videos, a full Integrated Review eText, and new Integrated Review worksheets are available to help students understand the objectives they missed on the Skills Check quiz. The Integrated Review eText includes review from Mike Sullivan’s developmental math series.
• A printed version of the Integrated Review eText is available for corequisite support as well. 
• NEW – Personal Inventory Assessments in the MyLab course are a collection of online exercises designed to promote self-reflection and engagement in students. These 33 assessments include topics such as a Stress Management Assessment, Diagnosing Poor Performance and Enhancing Motivation, and Time Management Assessment. Preparing for this Section quizzes verify that students have the prerequisite knowledge for the next section, and include page numbers for quick reference.
• Retain Your Knowledge problems help students in recalling skills learned earlier in the course, so that the material is fresh for the final exam. These appear periodically at the end of section exercises. 
• Video support in the course means that students have support anytime, anywhere.
• NEW – Lightboard videos featuring the author develop statistical concepts for students. 
• Author in the Classroom videos feature the author’s own lectures with his class, giving students an authentic lecture experience. Great for online courses or when students miss a lecture.
• UPDATED – Animated videos explain concepts or tie material learned earlier in the course with the upcoming chapter or section. Additional animated videos have been added to the 6th edition course. 
• Chapter Test Videos are available for each chapter test problem in complete, worked-out video solutions either solved by hand, using the TI-84C, or StatCrunch.

Abundant practice opportunities

Students learn best by doing – so ample opportunities for practice, often using real data to keep topics relevant and motivate students, are found throughout.

• NEW – Threaded Tornado Problems throughout the text present a single, large data set that measures various variables on all tornadoes that struck the United States in 2017. 
• Students learn various statistical techniques while using the same data set, showing how data can be manipulated to accomplish various tasks. 
• Marked with a tornado icon, these problems can be used as a semester-long project for students, giving them another opportunity to work with real data from recent events.
• Corresponding MyLab problems around this tornado data set are also available.
• NEW – Over 350 new and updated exercises are included, many of which focus more on students’ abilities to explain the results of their statistical analysis than on computation. In addition, exercises have been written to require students to understand pitfalls in faulty statistical analysis.
• Multiple types of exercises are used at the end of sections and chapters to test varying skills with progressive levels of difficulty. These exercises include Vocabulary and Skill Building, Applying the Concepts, and Explaining the Concepts. 
• Big Data Problems let students analyze data sets with more than 50 observations, which cover tens of thousands of observations with thousands of variables, giving them a taste of professional data analysis. These problems are marked with an icon and the data is available at www.pearsonhighered.com/sullivanstats.
• NEW – Additional data sets in the 6th Edition are larger and more complex to support modern data analysis. 
• NEW – Over 100 new and updated examples keep this text fresh and relevant for today’s students. Step-by-Step Annotated Examples guide students from problem to solution in three easy-to-follow steps: Problem, Approach, Solution. Solutions demonstrate using both by-hand and technology methods, where applicable.
• Chapter Review sections include a Chapter Summary, a list of key chapter Vocabulary, and Chapter Objectives with corresponding Review Exercises. A Chapter Test with video solutions ends each chapter. 
• Learning Catalytics™ is a student response tool integrated into the MyLab Statistics course 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. Search “SullivanStats” to use premade questions in Learning Catalytics written by Mike Sullivan for this title. 

Technology integration for optimal student support

Integration of technology in the text and MyLab course provides abundant support for students, no matter the statistical software being used in the course.

• NEW – R Manual—Written by Patrick Murphy (nephew of the author) and Michael Sullivan, the R Technology Guide provides a chapter-by-chapter discussion of R commands needed for each topic.
• Technology Step-by-Step guides show how to use StatCrunch, Minitab^®, Excel^®, and the TI-83/84 graphing calculator to complete statistics processes.
• Data sets with 12 or more observations are included in the MyLab course, or can be downloaded from the companion website, in multiple formats to allow for hands-on manipulation.
• Software output screens include displays from Minitab, TI-83/84, StatCrunch, and Excel to illustrate exercises and examples where appropriate.
• Technology Answers are now included where they differ from by-hand answers.
• Accompanying Technology Manuals contain detailed tutorial instructions and worked-out examples and exercises for TI-83/84 calculators.
• NEW – New Excel video solutions are available for any example in which Excel may be used to obtain statistical results.

Also available with MyLab Statistics

MyLab™ Statistics 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 Statistics personalizes the learning experience and improves results for each student. With MyLab Statistics and StatCrunch^® integrated web-based statistical software, students learn the skills they need to interact with data in the real world. Learn more about MyLab Statistics.

Teach your course your way

• 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, Minitab, R, and TI 83/84 calculators to complete exercises. There are also study cards available in MyLab Statistics for all of these plus JMP.

Empower each learner

• Features in MyLab Statistics get every student up to speed and ready to learn. The Getting Ready for Statistics question library contains more than 450 exercises that cover the relevant developmental math topics for a given section. And the Integrated Review content in the Sullivan Statistics course brings Mike Sullivan’s experience with corequisites into the MyLab, giving students robust review opportunities on prerequisites – including a full eText on prerequisite skills.

Deliver trusted content

• Exercises and resources in the MyLab are author-specific, written or produced by author Mike Sullivan to provide a completely seamless experience from text to MyLab. Author in the Classroom videos feature Mike Sullivan’s own classroom lectures. And new lightboard videos from the author present statistical concepts in a modern presentation format.

Author Mike Sullivan is involved in every aspect of the revision, including its online homework, supplements, videos, text narrative, and supporting corequisite materials.

• Over 350 new and updated exercises throughout the text — Also, students are now encouraged to write a few sentences that explain the results of their statistical analysis. 
• The answers in the back of the text provide recommended explanations of the statistical results. Not all the exercises are computational or require statistical analysis. 
• Many of the exercises have been written to require students to explain statistical concepts or understand pitfalls in faulty statistical analysis.
• Over 100 new and updated examples throughout the text, which follow the Problem, Approach, Solution presentation:
• Problem lays out the scenario of the example, Approach provides insight into the thought process behind the methodology used to solve the problem, and Solution goes through the solution utilizing the methodology suggested in the approach.
• New Threaded Tornado Problems throughout the text that present a single, large data set measuring various variables on all tornadoes that struck the United States in 2017:
• Marked with a tornado icon, these problems can be used as a semester-long project for students, and give them another opportunity to work with real data from recent events. 
• Corresponding MyLab problems around this tornado data set are also available.
• Optional Simulation & Randomization sections — To reflect the new approach of using simulation and randomization for hypothesis testing, the 6th Edition offers new optional sections online:
• Using simulation to test hypotheses for a population proportion (Section 10.2A) and population mean (Section 10.3A)
• Randomization methods for testing hypotheses for two independent proportions (Section 11.1A), two independent means (Section 11.3A), and the slope of the least-squares regression model (Section 14.1A).
• Classroom Notes — Instructors can use the new classroom notes to deliver lectures to students; students can print these notes out and bring them to class, which encourages good note-taking and allows them to focus on the concepts. The examples and activities in the classroom notes are different from those in the text and Instructor’s Resource Guide.
• Author-specific applets made for this course — These can be used in the classroom or as part of a project featured in the Activity Workbook, asking students to manipulate data to better understand concepts. New applet exercises in the MyLab encourage this exploration.
• R Manual — Written by Patrick Murphy (nephew of the author) and Michael Sullivan, the R Technology Guide provides a chapter-by-chapter discussion of R commands needed for each topic.
• Updated video program — Features new video types to provide more support to students:
• New lightboard videos featuring the author develop statistical concepts for students. 
• New Excel video solutions are available for any example in which Excel may be used to obtain statistical results.
• Updated animated videos explain concepts or tie material learned earlier in the course with the upcoming chapter or section. Additional animated videos have been added to the 6th edition course. 
• Additional data sets that are larger and more complex to support modern data analysis. 

Also available with MyLab Statistics

MyLab™ Statistics 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 Statistics personalizes the learning experience and improves results for each student. With MyLab Statistics and StatCrunch^® integrated web-based statistical software, students learn the skills they need to interact with data in the real world. Learn more about MyLab Statistics.

• New and updated MyLab problems — Written by the author, these utilize real data that is resampled from a larger data set. Sullivan also wrote new, assignable applet exercises that allow students to explore statistical concepts.
• Updated Integrated Review in the MyLab course — Offers corequisite support or can be used simply to get underprepared students up to speed. Based on the author’s own experience with corequisite courses, Integrated Review provides embedded and personalized review of prerequisite topics, selected by the author, within relevant chapters. In this revision, select topics have been added to provide further review. All assignments are premade and editable for instructors to assign.
• Premade, assignable Skills Check assignments check each student’s understanding of prerequisite skills needed to be successful in the following chapter. 
• For any gaps in skills that are identified, a personalized review homework is populated. Students receive personalized practice on the topics they need to focus on — no more, no less.
• For any topics a student may have gaps on, a suite of resources support student learning. Videos, a full Integrated Review eText, and new Integrated Review worksheets are available to help students understand the objectives they missed on the Skills Check quiz. The Integrated Review eText includes review from Mike Sullivan’s developmental math series.
• A printed version of the Integrated Review eText is available for corequisite support as well. 

• Personal Inventory Assessments in the MyLab course are a collection of online exercises designed to promote self-reflection and engagement in students. These 33 assessments include topics such as a Stress Management Assessment, Diagnosing Poor Performance and Enhancing Motivation, and Time Management Assessment. 

With training in mathematics, statistics, and economics, Mike Sullivan, III has a varied teaching background that includes 15 years of instruction in both high school- and college-level mathematics. He is currently a full-time professor of mathematics and statistics at Joliet Junior College. Mike has numerous textbooks in publication in addition to his Introductory Statistics Series – including a Developmental Math series and a Precalculus series which he writes with his father, Michael Sullivan.

Mike built this book in the classroom, using feedback from his students. He is well aware of the challenges of students taking an introductory statistics course. His goal is for students to be more informed interpreters of data, so they will become better decision-makers with stronger critical-thinking skills. When not in the classroom or writing, Mike enjoys spending time with his three children, Michael, Kevin, and Marissa, and playing golf.

Table of Contents

• Preface to the Instructor
• Resources for Success
• Applications Index

I. GETTING THE INFORMATION YOU NEED

1. Data Collection
   • 1.1 Introduction to the Practice of Statistics
   • 1.2 Observational Studies versus Designed Experiments
   • 1.3 Simple Random Sampling
   • 1.4 Other Effective Sampling Methods
   • 1.5 Bias in Sampling
   • 1.6 The Design of Experiments
   • Chapter 1 Review
   • Chapter Test
   • Making an Informed Decision: What College Should I Attend?
   • Case Study: Chrysalises for Cash

II. DESCRIPTIVE STATISTICS

1. Organizing and Summarizing Data
   • 2.1 Organizing Qualitative Data
   • 2.2 Organizing Quantitative Data: The Popular Displays
   • 2.3 Additional Displays of Quantitative Data
   • 2.4 Graphical Misrepresentations of Data
   • Chapter 2 Review
   • Chapter Test
   • Making an Informed Decision: Tables or Graphs?
   • Case Study: The Day the Sky Roared
2. Numerically Summarizing Data
   • 3.1 Measures of Central Tendency
   • 3.2 Measures of Dispersion
   • 3.3 Measures of Central Tendency and Dispersion from Grouped Data
   • 3.4 Measures of Position and Outliers
   • 3.5 The Five-Number Summary and Boxplots
   • Chapter 3 Review
   • Chapter Test
   • Making an Informed Decision: What Car Should I Buy?
   • Case Study: Who Was “A Mourner”?
3. Describing the Relation between Two Variables
   • 4.1 Scatter Diagrams and Correlation
   • 4.2 Least-Squares Regression
   • 4.3 Diagnostics on the Least-Squares Regression Line
   • 4.4 Contingency Tables and Association
   • 4.5 Nonlinear Regression: Transformations (online)
   • Chapter 4 Review
   • Chapter Test
   • Making an Informed Decision: Relationships among Variables on a World Scale
   • Case Study: Thomas Malthus, Population, and Subsistence

III. PROBABILITY AND PROBABILITY DISTRIBUTIONS

1. Probability
   • 5.1 Probability Rules
   • 5.2 The Addition Rule and Complements
   • 5.3 Independence and the Multiplication Rule
   • 5.4 Conditional Probability and the General Multiplication Rule
   • 5.5 Counting Techniques
   • 5.6 Simulating Probability Experiments
   • 5.7 Putting It Together: Which Method Do I Use?
   • 5.8 Bayes’s Rule (online)
   • Chapter 5 Review
   • Chapter Test
   • Making an Informed Decision: The Effects of Drinking and Driving
   • Case Study: The Case of the Body in the Bag
2. Discrete Probability Distributions
   • 6.1 Discrete Random Variables
   • 6.2 The Binomial Probability Distribution
   • 6.3 The Poisson Probability Distribution
   • 6.4 The Hypergeometric Probability Distribution (online)
   • 6.5 Combining Random Variables (online)
   • Chapter 6 Review
   • Chapter Test
   • Making an Informed Decision: Should We Convict?
   • Case Study: The Voyage of the St. Andrew
3. The Normal Probability Distribution
   • 7.1 Properties of the Normal Distribution
   • 7.2 Applications of the Normal Distribution
   • 7.3 Assessing Normality
   • 7.4 The Normal Approximation to the Binomial Probability Distribution
   • Chapter 7 Review
   • Chapter Test
   • Making an Informed Decision: Stock Picking
   • Case Study: A Tale of Blood Chemistry

IV. INFERENCE: FROM SAMPLES TO POPULATION

1. Sampling Distributions
   • 8.1 Distribution of the Sample Mean
   • 8.2 Distribution of the Sample Proportion
   • Chapter 8 Review
   • Chapter Test
   • Making an Informed Decision: How Much Time Do You Spend in a Day . . . ?
   • Case Study: Sampling Distribution of the Median
2. Estimating the Value of a Parameter
   • 9.1 Estimating a Population Proportion
   • 9.2 Estimating a Population Mean
   • 9.3 Estimating a Population Standard Deviation
   • 9.4 Putting It Together: Which Method Do I Use?
   • 9.5 Estimating with Bootstrapping
   • Chapter 9 Review
   • Chapter Test
   • Making an Informed Decision: How Much Should I Spend for this House?
   • Case Study: Fire-Safe Cigarettes
3. Hypothesis Tests Regarding a Parameter
   • 10.1 The Language of Hypothesis Testing
   • 10.2 Hypothesis Tests for a Population Proportion
   • 10.3 Hypothesis Tests for a Population Mean
   • 10.4 Hypothesis Tests for a Population Standard Deviation
   • 10.5 Putting It Together: Which Method Do I Use?
   • 10.6 The Probability of a Type II Error and the Power of the Test
   • 10.2A Using Simulation to Perform Hypothesis Tests on a Population Proportion (online)
   • 10.2B Hypothesis Tests for a Population Proportion Using the Normal Model (online)
   • 10.3A Using Simulation and the Bootstrap to Perform Hypothesis Tests on a Population Mean (online)
   • Chapter 10 Review
   • Chapter Test
   • Making an Informed Decision: Selecting a Mutual Fund
   • Case Study: How Old Is Stonehenge?
4. Inference on Two Population Parameters
   • 11.1 Inference about Two Population Proportions
   • 11.2 Inference about Two Means: Dependent Samples
   • 11.3 Inference about Two Means: Independent Samples
   • 11.4 Inference about Two Population Standard Deviations
   • 11.5 Putting It Together: Which Method Do I Use?
   • 11.1A Using Randomization Techniques to Compare Two Proportions (online)
   • 11.2A Using Bootstrapping to Conduct Inference on Two Dependent Means (online)
   • 11.3A Using Randomization Techniques to Compare Two Independent Means (online)
   • Chapter 11 Review
   • Chapter Test
   • Making an Informed Decision: Which Car Should I Buy?
   • Case Study: Control in the Design of an Experiment
5. Inference on Categorical Data
   • 12.1 Goodness-of-Fit Test
   • 12.2 Tests for Independence and the Homogeneity of Proportions
   • 12.3 Inference about Two Population Proportions: Dependent Samples
   • Chapter 12 Review
   • Chapter Test
   • Making an Informed Decision: Benefits of College
   • Case Study: Feeling Lucky? Well, Are You?
6. Comparing Three or More Means
   • 13.1 Comparing Three or More Means (One-Way Analysis of Variance)
   • 13.2 Post Hoc Tests on One-Way Analysis of Variance
   • 13.3 The Randomized Complete Block Design
   • 13.4 Two-Way Analysis of Variance
   • Chapter 13 Review
   • Chapter Test 687
   • Making an Informed Decision: Where Should I Invest?
   • Case Study: Hat Size and Intelligence
7. Inference on the Least-Squares Regression Model and Multiple Regression
   • 14.1 Testing the Significance of the Least-Squares Regression Model
   • 14.2 Confidence and Prediction Intervals
   • 14.3 Introduction to Multiple Regression
   • 14.4 Interaction and Dummy Variables
   • 14.5 Polynomial Regression
   • 14.6 Building a Regression Model
   • 14.1A Using Randomization Techniques on the Slope of the Least-Squares Regression Line (online)
   • Chapter 14 Review
   • Chapter Test
   • Making an Informed Decision: Buying a Home
   • Case Study: Housing Boom
8. Nonparametric Statistics
   • 15.1 An Overview of Nonparametric Statistics
   • 15.2 Runs Test for Randomness
   • 15.3 Inference about Measures of Central Tendency
   • 15.4 Inference about the Difference between Two Medians: Dependent Samples
   • 15.5 Inference about the Difference between Two Medians: Independent Samples
   • 15.6 Spearman’s Rank-Correlation Test
   • 15.7 Kruskal—Wallis Test
   • Chapter 15 Review
   • Chapter Test
   • Making an Informed Decision: Where Should I Live?
   • Case Study: Evaluating Alabama’s 1891 House Bill 504

Photo Credits

Appendix A Tables

Appendix B Lines (online)

Answers

Index

Additional information

Dimensions	0.90 × 8.40 × 10.70 in
Imprint	Pearson
Format	gen
ISBN-13	09780136625308
ISBN-10	0136625304
Author	Michael Sullivan III
Subjects	statistics, mathematics, higher education, Introductory Statistics