Prentice Hall has teamed the proven authorship and pedagogical expertise of Ron Larson with Betsy Farber's 30 years of statistics teaching experience to write an innovative and approachable text and state-of-the-art support package that will appeal to today's visually oriented and more technologically savvy students. Written for student success, every aspect of Elementary Statistics: Picturing the World has been carefully crafted to help students learn statistics.
Features :
NEW -- Real Statistics, Real Decisions features.
Challenges students to make decisions about which techniques to use shown in each chapter.
NEW -- Uses and Abuses features -- Shows practical applications specific to that chapter, and discusses common abuses.
NEW -- Revised and added coverage of z-scores.
Enhances students understanding of the material.
NEW -- Earlier treatment of P-values.
Allows for easier incorporation of a graphing calculator.
NEW -- Cleaner, more muted design.
Helps students navigate the text without overwhelming them.
NEW -- 20% more exercises.
Gives instructors a variety of problems to assign.
Motivational chapter openers -- Provides a roadmap and begins each chapter with a two page photographic description of a real-life problem that is revisited in the chapter.
Shows students how the chapter fits into the bigger picture of statistics by connecting it to topics learned in earlier chapters, and then gives them an overview of the chapter in the context of the real world data presented.
Titled examples paired with unique Try It Yourself problems -- Illustrates every concept in the text with one or more step-by-step examples that are numbered and titled for easy reference and immediately followed with a similar problem.
Enhances students' understanding of examples, and then gives them the opportunity to try one themselves right away.
Graphical approach -- Incorporates more than 750 graphical displays (more than twice as many as most introductory texts).
Helps students "picture" and understand the story the data has to tell, and presents corresponding graphs in place to prevent students from having to flip back and forth between pages.
Flexible technology -- Introduces each new technique with hand calculations before a worked Technology Example is presented.
Provides students with an understanding of the mathematical concepts behind the instant answer that technology tools provide. Gives instructors the freedom to determine the degree of technological dependency their individual course will require.
Technology project in each chapter -- Features a full-page technology assignment.
Gives students additional insight into the way technology is used to handle large data sets or complex, real-life questions. Provides more depth for instructors and students seeking to increase the technology flavor of the course.
Choice in presentation of "finding the area under a standard normal curve" -- Features the more student-friendly cumulative density function (CDF) table to find the area under the standard normal curve in section 5.2; and the more traditional 0-to-z table is included in Appendix A of the book.
Enables instructors to have flexibility in choosing whichever approach they prefer. Allows students to see fully worked examples for the chosen approach.
More than 1,700 exercises -- Includes a wide variety in each section that move from basic concepts and skill development to more challenging conceptual problems.
Graphical Reasoning exercises.
Tests students' ability to read and interpret graphs.
Extending the Basics exercises -- Concludes each section.
Challenges students to go beyond the material presented in the section.
Full-page chapter case study -- Includes actual data from a real-world context, and a series of thought-provoking questions that are designed to illustrate the important concepts of the chapter.
References interesting, real data, and allows students to use the case studies effectively as a springboard for group or individual projects and for classroom discussion.
"Picturing the World" mini case studies -- Illustrates the important concept or concepts of each section, and concludes with a question that links to the content.
Underscores the real-world importance of understanding statistics, and provides another effective vehicle for classroom discussion or student projects.
Author Bio
Ron Larson, : Penn State University at Erie
Farber, Elizabeth : Bucks County Community College
1. Introduction to Statistics.
An Overview of Statistics. Data Classification. Experimental Design.
2. Descriptive Statistics.
Frequency Distributions and Their Graphs. More Graphs and Displays. Measures of Central Tendency. Measures of Variation. Measures of Position.
3. Probability.
Basic Concepts of Probability. Conditional Probability and the Multiplication Rule. The Addition Rule. Counting Principles.
4. Discrete Probability Distributions.
Probability Distributions. Binomial Distributions. More Discrete Probability Distributions.
5. Normal Probability Distributions.
Introduction to Normal Distributions. The Standard Normal Distribution. Normal Distributions: Finding Probabilities. Normal Distribution: Finding Values. Normal Approximations to Binomial Distributions.
6. Confidence Intervals.
Confidence Intervals for the Mean (Large Samples). Confidence Intervals for the Mean (Small Samples). Confidence Intervals for Population Proportions. Confidence Intervals for Variance and Standard Deviation.
7. Hypothesis Testing with One Sample.
Introduction to Hypothesis Testing. Hypothesis Testing for the Mean (Large Samples). Hypothesis Testing for the Mean (Small Samples). Hypothesis Testing for Proportions. Hypothesis Testing for the Variance and Standard Deviation.
8. Hypothesis Testing with Two-Samples.
Testing the Difference Between Means (Large Independent Samples). Testing the Difference Between Means (Small Independent Samples). Testing the Difference Between Means (Dependent Samples). Testing the Difference Between Proportions.
9. Correlation and Regression.
Correlation. Linear Regression. Measures of Regression and Prediction Intervals. Multiple Regression.
10. Chi-Square Tests and the F-Distribution.
Goodness of Fit. Independence. Comparing Two Variances. Analysis of Variance.
11. Nonparametric Tests.
The Sign Test. The Wilcoxon Tests. The Kruskal-Wallis Test. Rank Correlation.
Prentice Hall has teamed the proven authorship and pedagogical expertise of Ron Larson with Betsy Farber's 30 years of statistics teaching experience to write an innovative and approachable text and state-of-the-art support package that will appeal to today's visually oriented and more technologically savvy students. Written for student success, every aspect of Elementary Statistics: Picturing the World has been carefully crafted to help students learn statistics.
Features :
NEW -- Real Statistics, Real Decisions features.
Challenges students to make decisions about which techniques to use shown in each chapter.
NEW -- Uses and Abuses features -- Shows practical applications specific to that chapter, and discusses common abuses.
NEW -- Revised and added coverage of z-scores.
Enhances students understanding of the material.
NEW -- Earlier treatment of P-values.
Allows for easier incorporation of a graphing calculator.
NEW -- Cleaner, more muted design.
Helps students navigate the text without overwhelming them.
NEW -- 20% more exercises.
Gives instructors a variety of problems to assign.
Motivational chapter openers -- Provides a roadmap and begins each chapter with a two page photographic description of a real-life problem that is revisited in the chapter.
Shows students how the chapter fits into the bigger picture of statistics by connecting it to topics learned in earlier chapters, and then gives them an overview of the chapter in the context of the real world data presented.
Titled examples paired with unique Try It Yourself problems -- Illustrates every concept in the text with one or more step-by-step examples that are numbered and titled for easy reference and immediately followed with a similar problem.
Enhances students' understanding of examples, and then gives them the opportunity to try one themselves right away.
Graphical approach -- Incorporates more than 750 graphical displays (more than twice as many as most introductory texts).
Helps students "picture" and understand the story the data has to tell, and presents corresponding graphs in place to prevent students from having to flip back and forth between pages.
Flexible technology -- Introduces each new technique with hand calculations before a worked Technology Example is presented.
Provides students with an understanding of the mathematical concepts behind the instant answer that technology tools provide. Gives instructors the freedom to determine the degree of technological dependency their individual course will require.
Technology project in each chapter -- Features a full-page technology assignment.
Gives students additional insight into the way technology is used to handle large data sets or complex, real-life questions. Provides more depth for instructors and students seeking to increase the technology flavor of the course.
Choice in presentation of "finding the area under a standard normal curve" -- Features the more student-friendly cumulative density function (CDF) table to find the area under the standard normal curve in section 5.2; and the more traditional 0-to-z table is included in Appendix A of the book.
Enables instructors to have flexibility in choosing whichever approach they prefer. Allows students to see fully worked examples for the chosen approach.
More than 1,700 exercises -- Includes a wide variety in each section that move from basic concepts and skill development to more challenging conceptual problems.
Graphical Reasoning exercises.
Tests students' ability to read and interpret graphs.
Extending the Basics exercises -- Concludes each section.
Challenges students to go beyond the material presented in the section.
Full-page chapter case study -- Includes actual data from a real-world context, and a series of thought-provoking questions that are designed to illustrate the important concepts of the chapter.
References interesting, real data, and allows students to use the case studies effectively as a springboard for group or individual projects and for classroom discussion.
"Picturing the World" mini case studies -- Illustrates the important concept or concepts of each section, and concludes with a question that links to the content.
Underscores the real-world importance of understanding statistics, and provides another effective vehicle for classroom discussion or student projects.
Author Bio
Ron Larson, : Penn State University at Erie
Farber, Elizabeth : Bucks County Community College
Table of Contents
1. Introduction to Statistics.
An Overview of Statistics. Data Classification. Experimental Design.
2. Descriptive Statistics.
Frequency Distributions and Their Graphs. More Graphs and Displays. Measures of Central Tendency. Measures of Variation. Measures of Position.
3. Probability.
Basic Concepts of Probability. Conditional Probability and the Multiplication Rule. The Addition Rule. Counting Principles.
4. Discrete Probability Distributions.
Probability Distributions. Binomial Distributions. More Discrete Probability Distributions.
5. Normal Probability Distributions.
Introduction to Normal Distributions. The Standard Normal Distribution. Normal Distributions: Finding Probabilities. Normal Distribution: Finding Values. Normal Approximations to Binomial Distributions.
6. Confidence Intervals.
Confidence Intervals for the Mean (Large Samples). Confidence Intervals for the Mean (Small Samples). Confidence Intervals for Population Proportions. Confidence Intervals for Variance and Standard Deviation.
7. Hypothesis Testing with One Sample.
Introduction to Hypothesis Testing. Hypothesis Testing for the Mean (Large Samples). Hypothesis Testing for the Mean (Small Samples). Hypothesis Testing for Proportions. Hypothesis Testing for the Variance and Standard Deviation.
8. Hypothesis Testing with Two-Samples.
Testing the Difference Between Means (Large Independent Samples). Testing the Difference Between Means (Small Independent Samples). Testing the Difference Between Means (Dependent Samples). Testing the Difference Between Proportions.
9. Correlation and Regression.
Correlation. Linear Regression. Measures of Regression and Prediction Intervals. Multiple Regression.
10. Chi-Square Tests and the F-Distribution.
Goodness of Fit. Independence. Comparing Two Variances. Analysis of Variance.
11. Nonparametric Tests.
The Sign Test. The Wilcoxon Tests. The Kruskal-Wallis Test. Rank Correlation.