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Introductory Statistics, MyLab Revision, 10th edition

Published by Pearson (January 1, 2019) © 2020

  • Neil A. Weiss Arizona State University

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For 1- or 2-semester courses in Introductory Statistics.

Statistically significant

Introductory Statistics, MyLab Revision, 10th Edition is ideal for courses that emphasize statistical reasoning and critical thinking. Weiss's meticulous and comprehensive coverage includes careful, detailed explanations with more than 1000 data sets and over 3000 exercises. The text takes a data-driven approach that encourages students to apply their knowledge and develop statistical understanding.

Weiss offers a parallel presentation of critical-value and P-value approaches to hypothesis testing. This unique design creates flexibility to concentrate on one approach or the opportunity for greater depth in comparing the two.

Hallmark features of this title

  • Real-World Examples illustrate every concept discussed in the text with detailed, compelling examples from real life.
  • You Try It! exercises follow most worked examples, allowing students to immediately check their understanding by directing them to a similar exercise to solve on their own.
  • Real Data Sources help students see the integration of statistics in everyday life, with carefully cited data from reputable journals, newspapers, magazines and websites.
  • Interpretation boxes explain the meaning and significance of statistical results in everyday life and highlight the importance of interpreting answers and results.
  • What Does It Mean? boxes explain the meaning of definitions, formulas, and key facts. This feature also summarizes relevant discussions.
  • Parallel Critical-Value/P-Value Approaches offer complete flexibility in the coverage of critical-value and P-value approaches to hypothesis testing. Instructors can focus on one approach or they can compare both approaches.

New and updated features of this title

  • Procedure boxes have been enhanced to include the “why, when, and how” of the statistical methods. Each procedure box has a brief identifying title followed by a statement of its purpose (why it's used), the assumptions for its use (when it's used), and the steps for applying the procedure (how it's used).
  • The Technology Center features in this edition reflect the latest software releases for Minitab®, Excel® and the TI-83/84 Plus. This in-text feature includes step-by-step instructions for the implementation of each of these three applications.
  • 50% of the chapter-opening case studies are new for this edition.
  • More than 35% of the exercises are new, updated or modified. This edition contains more than 3000 high-quality exercises, which far exceeds what is found in typical introductory statistics books.
  • Expanded Warm-up Exercises: Hundreds of “warm-up” exercises have been added. These exercises provide context-free problems that allow students to concentrate solely on the relevant concepts before moving on to applied exercises.
  • Expanded TI Programs created by the author allow users of the popular TI-83/84 Plus to perform additional statistical analyses with their calculators. Those programs are downloadable from the TI Programs section of the WeissStats Resource Site.

Features of MyLab Statistics for the 10th Edition

  • StatCrunch® Reports (now with assignable MyLab Statistics questions) 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 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. Questions from each project can also be assigned individually.
  • Text-Specific Applets are powerful tools for exploring statistical concepts and enhancing understanding. All text-specific applets for Introductory Statistics were updated and converted to HTML5, making them more user friendly and made assignable in MyLab Statistics.
  • Interactive Applet Modules introduce students to a concept, walk them through an example, and close by asking them to answer a series of application questions. Interactive Applet Modules are assignable along with the text-specific applets and 13 standalone StatCrunch applets.

* Indicates optional material.

** Indicates optional material on the WeissStats site.

PART I: INTRODUCTION

  • 1. The Nature of Statistics
    • Case Study: Top Films of All Time
    • 1.1 Statistics Basics
    • 1.2 Simple Random Sampling
    • 1.3 Other Sampling Designs*
    • 1.4 Experimental Designs*
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography

PART II: DESCRIPTIVE STATISTICS

  • 2. Organizing Data
    • Case Study: World's Richest People
    • 2.1 Variables and Data
    • 2.2 Organizing Qualitative Data
    • 2.3 Organizing Quantitative Data
    • 2.4 Distribution Shapes
    • 2.5 Misleading Graphs*
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  • 3. Descriptive Measures
    • Case Study: The Beatles' Song Length
    • 3.1 Measures of Center
    • 3.2 Measures of Variation
    • 3.3 Chebyshev's Rule and the Empirical Rule*
    • 3.4 The Five-Number Summary; Boxplots
    • 3.5 Descriptive Measures for Populations; Use of Samples
    • Chapter in Review
    • Review Problems
    • Focusing on Data
    • Analysis
    • Case Study Discussion
    • Biography

PART III: PROBABILITY, RANDOM VARIABLES, AND SAMPLING DISTRIBUTIONS

  • 4. Probability Concepts
    • Case Study: Texas Hold'em
    • 4.1 Probability Basics
    • 4.2 Events
    • 4.3 Some Rules of Probability
    • 4.4 Contingency Tables; Joint and Marginal Probabilities*
    • 4.5 Conditional Probability*
    • 4.6 The Multiplication Rule; Independence*
    • 4.7 Bayes's Rule*
    • 4.8 Counting Rules*
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  • 5. Discrete Random Variables*
    • Case Study: Aces Wild on the Sixth at Oak Hill
    • 5.1 Discrete Random Variables and Probability Distributions*
    • 5.2 The Mean and Standard Deviation of a Discrete Random Variable*
    • 5.3 The Binomial Distribution*
    • 5.4 The Poisson Distribution*
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  • 6. The Normal Distribution
    • Case Study: Chest Sizes of Scottish Militiamen
    • 6.1 Introducing Normally Distributed Variables
    • 6.2 Areas under the Standard Normal Curve
    • 6.3 Working with Normally Distributed Variables
    • 6.4 Assessing Normality; Normal Probability Plots
    • 6.5 Normal Approximation to the Binomial Distribution*
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  • 7. The Sampling Distribution of the Sample Mean
    • Case Study: The Chesapeake and Ohio Freight Study
    • 7.1 Sampling Error; the Need for Sampling Distributions
    • 7.2 The Mean and Standard Deviation of the Sample Mean
    • 7.3 The Sampling Distribution of the Sample Mean
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography

PART IV: INFERENTIAL STATISTICS

  • 8. Confidence Intervals for One Population Mean
    • Case Study: Bank Robberies: A Statistical Analysis
    • 8.1 Estimating a Population Mean
    • 8.2 Confidence Intervals for One Population Mean When σ Is Known
    • 8.3 Confidence Intervals for One Population Mean When σ Is Unknown
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  • 9. Hypothesis Tests for One Population Mean
    • Case Study: Gender and Sense of Direction
    • 9.1 The Nature of Hypothesis Testing
    • 9.2 Critical-Value Approach to Hypothesis Testing
    • 9.3 P-Value Approach to Hypothesis Testing
    • 9.4 Hypothesis Tests for One Population Mean When σ Is Known
    • 9.5 Hypothesis Tests for One Population Mean When σ Is Unknown
    • 9.6 The Wilcoxon Signed-Rank Test*
    • 9.7 Type II Error Probabilities; Power*
    • 9.8 Which Procedure Should Be Used?**
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  • 10. Inferences for Two Population Means
    • Case Study: Dexamethasone Therapy and IQ
    • 10.1 The Sampling Distribution of the Difference between Two Sample Means for Independent Samples
    • 10.2 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Assumed Equal
    • 10.3 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Not Assumed Equal
    • 10.4 The Mann - Whitney Test*
    • 10.5 Inferences for Two Population Means, Using Paired Samples
    • 10.6 The Paired Wilcoxon Signed-Rank Test*
    • 10.7 Which Procedure Should Be Used?**
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  • 11. Inferences for Population Standard Deviations*
    • Case Study: Speaker Woofer Driver Manufacturing
    • 11.1 Inferences for One Population Standard Deviation*
    • 11.2 Inferences for Two Population Standard Deviations, Using Independent Samples*
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  • 12. Inferences for Population Proportions
    • Case Study: Arrested Youths
    • 12.1 Confidence Intervals for One Population Proportion
    • 12.2 Hypothesis Tests for One Population Proportion
    • 12.3 Inferences for Two Population Proportions
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  • 13. Chi-Square Procedures
    • Case Study: Eye and Hair Color
    • 13.1 The Chi-Square Distribution
    • 13.2 Chi-Square Goodness-of-Fit Test
    • 13.3 Contingency Tables; Association
    • 13.4 Chi-Square Independence Test
    • 13.5 Chi-Square Homogeneity Test
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography

PART V: REGRESSION, CORRELATION, AND ANOVA

  • 14. Descriptive Methods in Regression and Correlation
    • Case Study: Healthcare: Spending and Outcomes
    • 14.1 Linear Equations with One Independent Variable
    • 14.2 The Regression Equation
    • 14.3 The Coefficient of Determination
    • 14.4 Linear Correlation
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  • 15. Inferential Methods in Regression and Correlation
    • Case Study: Shoe Size and Height
    • 15.1 The Regression Model; Analysis of Residuals
    • 15.2 Inferences for the Slope of the Population Regression Line
    • 15.3 Estimation and Prediction
    • 15.4 Inferences in Correlation
    • 15.5 Testing for Normality**
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography
  • 16. Analysis of Variance (ANOVA)
    • Case Study: Self-Perception and Physical Activity
    • 16.1 The F-Distribution
    • 16.2 One-Way ANOVA: The Logic
    • 16.3 One-Way ANOVA: The Procedure
    • 16.4 Multiple Comparisons*
    • 16.5 The Kruskal - Wallis Test*
    • Chapter in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Biography

PART VI: MULTIPLE REGRESSION AND MODEL BUILDING; EXPERIMENTAL DESIGN AND ANOVA**

  • MODULE A: Multiple Regression Analysis
    • Case Study: Automobile Insurance Rates
    • A.1 The Multiple Linear Regression Model
    • A.2 Estimation of the Regression Parameters
    • A.3 Inferences Concerning the Utility of the Regression Model
    • A.4 Inferences Concerning the Utility of Particular Predictor Variables
    • A.5 Confidence Intervals for Mean Response; Prediction Intervals for Response
    • A.6 Checking Model Assumptions and Residual Analysis
    • Module in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Answers to Selected Exercises
    • Index
  • MODULE B: Model Building in Regression
    • Case Study: Automobile Insurance Rates Revisited
    • B.1 Transformations to Remedy Model Violations
    • B.2 Polynomial Regression Model
    • B.3 Qualitative Predictor
    • B.4 Multicollinearity
    • B.5 Model Selection: Stepwise Regression
    • B.6 Model Selection: All-Subsets Regression
    • B.7 Pitfalls and Warnings
    • Module in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion
    • Answers to Selected Exercises
    • Index
  • MODULE C: Design of Experiments and Analysis of Variance
    • Case Study: Dental Hygiene: Which Toothbrush?
    • C.1 Factorial Designs
    • C.2 Two-Way ANOVA: The Logic
    • C.3 Two-Way ANOVA: The Procedure
    • C.4 Two-Way ANOVA: Multiple Comparisons
    • C.5 Randomized Block Designs
    • C.6 Randomized Block ANOVA: The Logic
    • C.7 Randomized Block ANOVA: The Procedure
    • C.8 Randomized Block ANOVA: Multiple Comparisons
    • C.9 Friedman's Nonparametric Test for the Randomized Block Design
    • Module in Review
    • Review Problems
    • Focusing on Data Analysis
    • Case Study Discussion

Answers to Selected Exercises

Index

Appendices

  • A: Statistical Tables
  • B: Answers to Selected Exercises

Index

Photo Credits

* Indicates optional material.

** Indicates optional material on the WeissStats site.

About our author

The late Neil A. Weiss received his Ph.D. from UCLA and subsequently accepted an assistant professor position at Arizona State University (ASU), where he was ultimately promoted to the rank of full professor. Dr. Weiss taught statistics, probability, and mathematics, from the freshman level to the advanced graduate level, for more than 30 years.

In recognition of his excellence in teaching, Dr. Weiss received the Dean's Quality Teaching Award from the ASU College of Liberal Arts and Sciences. He also was runner-up twice for the Charles Wexler Teaching Award in the ASU School of Mathematical and Statistical Sciences. Dr. Weiss's comprehensive knowledge and experience ensure that his texts are mathematically and statistically accurate, as well as pedagogically sound.

In addition to his numerous research publications, Dr. Weiss was the author of A Course in Probability (Addison-Wesley, 2006). He also authored or coauthored books in finite mathematics, statistics and real analysis. His texts, well known for their precision, readability and pedagogical excellence, are used worldwide.

Dr. Weiss was a pioneer of the integration of statistical software into textbooks and the classroom, first providing such integration in the book Introductory Statistics (AddisonWesley,1982). Since this first publication, Neil Weiss's work continues to inspire future statisticians and current students of statistics alike.

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