Interactive Statistics: Informed Decisions Using Data, 2nd edition

Published by Pearson (January 11, 2018) © 2019

  • Michael Sullivan Joliet Junior College

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For courses in Introductory Statistics.

Gets students to do statistics actively as they learn

Interactive Statistics: Informed Decisions Using Data, 2nd Edition presents content in a way that gets students actively doing statistics as they encounter new concepts. Written fully in MyLab Statistics, it combines text, multimedia and assessment into a seamless learning experience. Through a series of Interactive Assignments, students are encouraged to experience statistics in new and dynamic ways. This practical approach paired with the interactive, guided learning environment helps improve conceptual understanding, knowledge retention and ability to connect statistics to the world at large.

Hallmark features of this title

  • Interactive Assignments for each section of a chapter cycle through a “read a little, watch a little, do a little” model. Students read text, interact with multimedia and step-by-step examples, and complete assessment questions for each objective.
    • Preparing for This Section provides review and exercises to assess mastery of prerequisite topics.
    • Learning Objectives for This Section previews the learning objectives in the Interactive Assignment.
  • The Interactive eText offers the text and multimedia from the Interactive Assignments without the built-in assessment.
    • The Guided Notebook helps students record key information from the Interactive Assignments and take good notes.
    • The Student Activity Workbook includes classroom and applet activities.

New and updated features of this title

  • Redesigned Chapter Review section makes it easier for students to navigate through the Chapter Summary video and downloadable MindMap, list of key chapter Vocabulary and Formulas, Chapter Objectives with corresponding review exercises, Review Exercises, Chapter Test with complete, worked-out answers, and Chapter Review Quiz that populates a personalized homework based on each student's strengths and weaknesses.
  • New User Guidance Video explains how to navigate through the Interactive Assignments and get the most from them.
  • New Simulations-based Interactive Assignments can be assigned at the instructor's discretion.
  • New downloadable Classroom Notes from Mike Sullivan's classroom lectures when using Interactive Statistics are available.
  • New and enhanced Interactive Assignments include expanded embedded simulation and applet activities, new innovative lightboard videos, new Excel video solutions, new animations and expanded Reading Assessment questions.

Features of MyLab Statistics for the 2nd Edition

  • NEW - StatCrunch Question Library: This library of questions provides opportunities for students to analyze and interpret data sets in StatCrunch.
    • Instructors can assign individual questions from the library by topic or they can assign questions from the same data set as a longer assignment that spans multiple learning objectives.
  • NEW - Pre-built Learning Catalytics modules for each chapter and more questions:
    • Learning Catalytics is a student response tool that uses smartphones, tablets or laptops to engage students in more interactive tasks and thinking during lecture. It fosters student engagement and peer-to-peer learning with real-time analytics.

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 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 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
    • 3.5 The Five-Number Summary and Boxplots
    • Chapter 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
    • Chapter 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 Simulation
    • 5.7 Putting It Together: Which Method Do I Use?
    • Chapter Review
    • Chapter Test
    • Making an Informed Decision: What Are 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
    • Chapter 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 Review
    • Chapter Test
    • Making an Informed Decision: What Stock Do I Pick?
    • Case Study: A Tale of Blood, Chemistry, and Health

IV: INFERENCE – FROM SAMPLES TO POPULATION

  1. Sampling Distributions
    • 8.1 Distribution of the Sample Mean
    • 8.2 Distribution of the Sample Proportion
    • Chapter Review
    • Chapter Test
    • Making an Informed Decision: How Would You Break Down Your Day?
    • Case Study: Sampling Distribution of the Median
  2. Estimating the Value of a Parameter Using Confidence Intervals
    • 9.1 Estimating a Population Proportion
    • 9.2 Estimating a Population Mean
    • 9.3 Putting It Together: Which Procedure Do I Use?
    • 9.4 Estimating with Bootstrapping
    • Chapter Review
    • Chapter Test
    • Making an Informed Decision: How Much Should I Spend for this House?
    • Case Study: When Model Requirements Fail
  3. Hypothesis Tests Regarding a Parameter
    • 10.1 The Language of Hypothesis Testing
    • 10.2A Hypothesis Tests on a Population Proportion with Simulation
    • 10.2B Hypothesis Tests on a Population Proportion Using the Normal Model
    • 10.3A Using Simulation/Bootstrapping in Hypothesis Tests for a Population Mean
    • 10.3B Hypothesis Tests for a Population Mean
    • 10.4 Putting It Together: Which Procedure Do I Use?
    • Chapter Review
    • Chapter Test
    • Making an Informed Decision: Selecting a Mutual Fund
    • Case Study: How Old Is Stonehenge?
  4. Inference on Two Samples
    • 11.1A Using Randomization Techniques to Compare Two Proportions
    • 11.1 Inference about Two Population Proportions: Independent Samples
    • 11.2A Using Bootstrapping to Conduct Inference on Two Dependent Means
    • 11.2 Inference about Two Population Means: Dependent Samples
    • 11.3A Using Randomization Techniques to Compare Two Independent Means
    • 11.3 Inference about Two Population Means: Independent Samples
    • 11.4 Putting It Together: Which Procedure Do I Use?
    • Chapter Review
    • Chapter Test
    • Making an Informed Decision: Which Car Should I Buy?
    • Case Study: Control in the Design of 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 Review
    • Chapter Test
    • Making an Informed Decision: What Are the 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
    • Chapter Review
    • Chapter Test
    • Making an Informed Decision: Where Should I Invest?
    • Case Study: Hat Size and Intelligence
  7. Inference of the Least-Squares Regression Model
    • 14.1A Using Randomization Techniques on the Slope of the Least-Squares Regression Line
    • 14.1 Testing the Significance of the Least-Squares Regression Model
    • 14.2 Confidence and Prediction Intervals
    • Chapter Review
    • Chapter Test
    • Making an Informed Decision: Buying a Home
    • Case Study: Housing Boom

APPENDICES

  • A. Tables
  • B. Lines
  • C. Additional Topics
    • C.1 The Normal Approximation to the Binomial Probability Distribution
    • C.2 Estimating a Population Standard Deviation
    • C.3 Hypothesis Tests for a Population Standard Deviation

About our authors

Michael Sullivan, III has training in mathematics, statistics and economics, with a varied teaching background that includes 27 years of instruction in both high school- and college-level mathematics. He is currently a full-time professor of mathematics at Joliet Junior College. Michael has numerous textbooks in publication, including an Introductory Statistics series and a Precalculus series which he writes with his father, Michael Sullivan.

Michael believes that his experiences writing texts for college-level math and statistics courses give him a unique perspective on where students are headed once they leave the developmental mathematics tract. This experience is reflected in the philosophy and presentation of his developmental text series. When not in the classroom or writing, Michael enjoys spending time with his 3 children, Michael, Kevin and Marissa, and playing golf. Now that his 2 sons are getting older, he has the opportunity to do both at the same time!

George Woodbury earned a bachelor's degree in Mathematics from the University of California - Santa Barbara and a master's degree in Mathematics from California State University - Northridge. He currently teaches at College of the Sequoias in Visalia, CA, just outside of Fresno. George has been honored as an instructor by both his students and his colleagues. Aside from teaching and writing, George served as the department chair of the math/engineering division from 1999 through 2004. He has been a user of MyLab Math and MyLab Statistics since inception, continually coming up with creative ways to integrate his teaching methods with technology. He actively blogs his thoughts on math, statistics, teaching and study skills. 

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