Teaching Statistics and Probability

(Yearbook - National Council of Teachers of Mathematics)
Albert P. Shulte e James R. Smart

National Council of Teachers of Mathematics | 1981 | 258 páginas | rar - pdf | 7,22 Mb

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This 1981 yearbook of the National Council of Teachers of Mathematics (NCTM) offers classroom ideas for teaching statistics and probability, viewed as important topics in the school mathematics curriculum. Statistics and probability are seen as appropriate because they: (1) provide meaningful applications of mathematics at all levels; (2) provide methods for dealing with uncertainty; (3) give us some understanding of the statistical arguments, good and bad, with which we are continually bombarded; (4) help consumers distinguish sound use of statistical procedures for unsound or deceptive uses; and (5) are inherently interesting, exciting, and motivating topics for most students. The text is divided into eight parts, labeled: (1) The Case for Teaching Statistics and Probability; (2) Samples of Existing Courses or Programs; (3) Classroom Activities; (4) Teaching and Learning Specific Topics; (5) Applications; (6) Statistical Inference; (7) Monte Carlo Techniques and Simulation; and (8) Using Computers. The yearbook concludes with a bibliography and a list of suggested class projects

Understand Statistics: Teach Yourself

Alan Graham

Blacklick, OH : McGraw-Hill | 2010 | 380 páginas | rar - pdf | 1 Mb

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A straightforward introduction to the principles of this vital field of mathematics. Assuming minimal prior knowledge and using examples which put the theory into context, this book makes even complex concepts and techniques easy to grasp

Contents
Introducing statistics
Some basic maths
Graphing data
Choosing a suitable graph
Summarizing data
Lies and statistics
Choosing a sample
Collecting information
Spreadsheets to the rescue
Reading tables of data
Regression: describing relationships between things
Correlation: measuring the strength of a relationship
Chance and probability
Probability models
Deciding on differences.

Super Crunchers Why Thinking by Numbers Is the New Way to Be Smart

 Ian Ayres

Bantam | 2007 | 211 páginas | rar - epub | 601 kb

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pdf - 3,5 Mb

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An international sensation—and still the talk of the relevant blogosphere—this Wall Street Journal and New York Timesbusiness bestseller examines the “power” in numbers. Today more than ever, number crunching affects your life in ways you might not even imagine. Intuition and experience are no longer enough to make the grade. In order to succeed—even survive—in our data-based world, you need to become statistically literate.

Cutting-edge organizations are already crunching increasingly larger databases to find the unseen connections among seemingly unconnected things to predict human behavior with staggeringly accurate results. From Internet sites like Google and Amazon that use filters to keep track of your tastes and your purchasing history, to insurance companies and government agencies that every day make decisions affecting your life, the brave new world of the super crunchers is happening right now. No one who wants to stay ahead of the curve should make another keystroke without reading Ian Ayres’s engrossing and enlightening book.

Contents

1   Who’s Doing Your Thinking for You?

2   Creating Your Own Data with the Flip of a Coin

3   Government by Chance

4   How Should Physicians Treat Evidence-Based Medicine?

5   Experts Versus Equations

6   Why Now?

7   Are We Having Fun Yet?

8   The Future of Intuition (and Expertise)

Help Your Kids with Math: A visual problem solver for kids and parents

 

Barry Lewis

DK Publishing | 2010 | 258 páginas | rar - pdf | 9,7 Mb

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Studying math is often a source of great anxiety for children and also proves troublesome for parents helping with their homework.

Using uniquely accessible illustrated stress-free approach, Help Your Kids with Math looks at every aspect of math, from simple sums to simultaneous equations, and explains each facet in easily understandable language so that adults and kids can master the subject together.

In Help Your Kids with Math tricky concepts are explored and examined step-by-step, so that even the most math-phobic individual will be able to approach and solve complex problems with confidence.

Contents
NUMBERS
Introducing numbers ; Addition ; Subtraction ; Multiplication ; Division ; Prime numbers ; Units of measurement ; Positive and negative numbers ; Powers and roots ; Standard form ; Decimals in action; Fractions, Ratio and proportion, Percentages, Converting fractions, decimals, and percentages ; Mental math ; Rounding off ; Using a calculator ; Personal finance ; Business finance
GEOMETRY
What is geometry?; Angles; Straight lines; Symmetry; Coordinates; Vectors; Translations ; Rotations; Reflections; Enlargements; Scale drawings; Bearings; Constructions; Loci ; Triangles; Constructing triangles; Congruent triangles; Area of a triangle; Similar triangles ; Pythagorean Theorem ; Quadrilaterals; Polygons ; Circles ; Circumference and diameter ; Area of a circle ; Angles in a circle; Chords and cyclic quadrilaterals ; Tangents ; Arcs ; Sectors ; Solids ; Volumes ; Surface area 148
TRIGONOMETRY
What is trigonometry? ; Working with trigonometry ; Finding missing sides ; Finding missing angles 
ALGEBRA
What is algebra?; Sequences; Working with expressions; Expanding and factorizing expressions; Quadratic expressions; Formulas; Solving equations; Linear graphs; Simultaneous equations; Factorizing quadratic equations; The quadratic formula; Quadratic graphs ; Inequalities 
STATISTICS
What is statistics? ; Collecting and organizing data ; Bar charts ; Pie charts ; Line graphs;  Averages; Moving Averages ; Measuring spread ; Histograms ; Scatter diagrams 
PROBABILITY
What is probability? , Expectation and reality ; Multiple probability ; Dependent events ; Tree diagrams 
Reference section 232
Glossary 244
Index 252
Acknowledgments 256

Graphic Discovery a trout in the milk and other visual adventures

 

Howard Wainer

Princeton University Press | 2004 | 209 páginas | rar - pdf |7,7 Mb

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Good graphs make complex problems clear. From the weather forecast to the Dow Jones average, graphs are so ubiquitous today that it is hard to imagine a world without them. Yet they are a modern invention. This book is the first to comprehensively plot humankind's fascinating efforts to visualize data, from a key seventeenth-century precursor--England's plague-driven initiative to register vital statistics--right up to the latest advances. In a highly readable, richly illustrated story of invention and inventor that mixes science and politics, intrigue and scandal, revolution and shopping, Howard Wainer validates Thoreau's observation that circumstantial evidence can be quite convincing, as when you find a trout in the milk.

The story really begins with the eighteenth-century origins of the art, logic, and methods of data display, which emerged, full-grown, in William Playfair's landmark 1786 trade atlas of England and Wales. The remarkable Scot singlehandedly popularized the atheoretical plotting of data to reveal suggestive patterns--an achievement that foretold the graphic explosion of the nineteenth century, with atlases published across the observational sciences as the language of science moved from words to pictures.

Next come succinct chapters illustrating the uses and abuses of this marvelous invention more recently, from a murder trial in Connecticut to the Vietnam War's effect on college admissions. Finally Wainer examines the great twentieth-century polymath John Wilder Tukey's vision of future graphic displays and the resultant methods--methods poised to help us make sense of the torrent of data in our information-laden world.

Contents

Preface xiii

Introduction 1

In the sixteenth century, the bubonic plague provided the motivation for the English to begin gathering data on births, marriages, and deaths. These data, the Bills of Mortality, were the grist that Dr. John Arbuthnot used to prove the existence of God. Unwittingly, he also provided strong evidence that data graphs were not yet part of a scientist’s tools.

Part I William Playfair and the Origins of Graphical Display

1 Why Playfair? 9

All of the pieces were in place for the invention of statistical graphics long before Playfair was born. Why didn’t anyone else invent them? Why did Playfair?

2 Who Was Playfair? 20

by Ian Spence and Howard Wainer

William Playfair (1759–1823) was an inventor and ardent advocate of statistical graphics. Here we tell a bit about his life.

3 William Playfair: A Daring Worthless Fellow 24

by Ian Spence and Howard Wainer

Audacity was an important personality trait for the invention of graphics because the inventor had to move counter to the Cartesian approach to science. We illustrate this quality in Playfair by describing his failed attempt to blackmail one of the richest lords of Great Britain.

4 Scaling the Heights (and Widths) 28

The message conveyed by a statistical graphic can be distorted by manipulating the aspect ratio, the ratio of a graph’s width to its height. Playfair deployed this ability in a masterly way, providing a guide to future display technology.

5 A Priestley View of International Currency Exchanges 39

A recent plot of the operating hours of international currency exchanges confuses matters terribly. Why? We find that when we use a different graphical form, developed by Joseph Priestley in 1765, the structure becomes clear. We also learn how Priestley discovered the latent graphicacy in his (and our) audiences.

6 Tom’s Veggies and the American Way 44

European intellectuals were not the only ones graphing data. During a visit to Paris (and prompted by letters from Benjamin Franklin), Thomas Jefferson learned of this invention and he later put it to a more practical use than the depiction of the life spans of heroes from classical antiquity.

7 The Graphical Inventions of Dubourg and Ferguson: Two Precursors to William Playfair 47

Although he developed the line chart independently, Priestley was not the first to do so. The earliest seems to be the Parisian physician Jacques Barbeau-Dubourg (1709–1779), who created a wonderful

graphical scroll in 1753. Graphical representation must have been in the air, for the Scottish philosopher Adam Ferguson (1723–1816) added his version of time lines to the mix in 1780.

8 Winds across Europe: Francis Galton and the Graphic Discovery of Weather Patterns 52

In 1861, Francis Galton organized weather observatories throughout Western Europe to gather data in a standardized way. He organized these data and presented them as a series of ninety-three maps and charts, from which he confirmed the existence of the anticyclonic movement of winds around a low-pressure zone.

Part II Using Graphical Displays to Understand the Modern World

9 A Graphical Investigation of the Scourge of Vietnam 59

During the Vietnam War, average SAT scores went down for those students who were not in the military. In addition, the average ASVAB scores (the test used by the military to classify all members of the military) also declined. This Lake Wobegon–like puzzle is solved graphically.

10 Two Mind-Bending Statistical Paradoxes 63

The odd phenomenon observed with test scores during the Vietnam War is not unusual. We illustrate this seeming paradox with other instances, show how to avoid them, and then discuss an even subtler statistical pitfall that has entrapped many illustrious would-be data analysts.

11 Order in the Court 72

How one orders the elements of a graph is critical to its comprehensibility. We look at a New York Times graphic depicting the voting records of U.S. Supreme Court justices and show that reordering the graphic provides remarkable insight into the operation of the court.

12 No Order in the Court 78

We examine one piece of the evidence presented in the 1998 murder trial of State v. Gibbs and show how the defense attorneys, by misordering the data in the graph shown to the judge, miscommunicated a critical issue in their argument.

13 Like a Trout in the Milk 81

Thoreau pointed out that sometimes circumstantial evidence can be quite convincing, as when you find a trout in the milk. We examine a fascinating graph that provides compelling evidence of industrial malfeasance.

14 Scaling the Market 86

We examine the stock market and show that different kinds of scalings provide the answers to different levels of questions. One long view suggests a fascinating conjecture about the trade-offs between investing in stocks and investing in real estate.

15 Sex, Smoking, and Life Insurance: A Graphical View 90

We examine two risk factors for life insurance—sex and smoking— and uncover the implicit structure that underlies insurance premiums.

16 There They Go Again! 97

The New York Times is better than most media sources for statistical graphics, but even the Times has occasional relapses to an earlier time in which confusing displays ran rampant over its pages. We discuss some recent slips and compare them with prior practice.

17 Sex and Sports: How Quickly Are Women Gaining? 103

A simple graph of winning times in the Boston Marathon augmented by a fitted line provides compelling, but incorrect, evidence for the relative gains that women athletes have made over the past few decades. A more careful analysis provides a better notion of the changing size of the sex differences in athletic performances.

18 Clear Thinking Made Visible: Redesigning Score Reports for Students 109

Too often communications focus on what the transmitter thinks is important rather than on what the receiver is most critically interested in. The standard SAT score report that is sent to more than one million high school students annually is one such example. Here we revise this report using principles abstracted from another missive sent to selected high school students.

Part III Graphical Displays in the Twenty-first Century

The three chapters of this section grew out of a continuing conversation with John W. Tukey, the renowned Princeton polymath, on the graphical tools that were likely to be helpful when data were

displayed on a computer screen rather than a piece of paper. These conversations began shortly after Tukey’s eighty-fourth birthday and continued for more than a year, ending the night before he died.

19 John Wilder Tukey: The Father of Twenty-first-Century Graphical Display 117

20 Graphical Tools for the Twenty-first Century: I. Spinning and Slicing 125

21 Graphical Tools for the Twenty-first Century: II. Nearness and Smoothing Engines 134

22 Epilogue: A Selection of Selection Anomalies 142

Graphical displays are only as good as the data from which they are composed. In this final chapter we examine an all too frequent data flaw. The effects of nonsampling errors deserve greater attention,

especially when randomization is absent. Formal statistical analysis treats only some of the uncertainties. In this chapter we describe three examples of how flawed inferences can be made

from nonrandomly obtained samples and suggest a strategy to guard against flawed inferences.
Conclusion 150
Dramatis Personae 151
This graphical epic has more than one hundred characters. Some play major roles, but most are cameos. To help keep straight who is who, this section contains thumbnail biographies of all the players.
Notes 173
References 177

Index 185

Leveled Texts for Mathematics Data Analysis and Probability

Stephanie Paris

Shell Education | 2011 | 147 páginas | rar -pdf | 23 Mb

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Highlighting data analysis and probability, this resource provides the know-how to use leveled texts to differentiate instruction in mathematics. A total of 15 different topics are featured in and the high-interest text is written at four different reading levels with matching visuals. Practice problems are provided to reinforce what is taught in the passage. The included Teacher Resource CD features a modifiable version of each passage in text format and full-color versions of the texts and image files. This resource is correlated to the Common Core State Standards.

Table of Contents
What Is Differentiation?......4
How to Differentiate Using This Product.......5
General Information About the Student Populations........6
Below-Grade-Level Students........6
English Language Learners.......6
On-Grade-Level Students........7
Above-Grade-Level Students........7
Strategies for Using the Leveled Texts......8
Below-Grade-Level Students.......8
English Language Learners....... 11
Above-Grade-Level Students..... 14
How to Use This Product...... 16
Readability Chart........ 16
Components of the Product......... 17
Tips for Managing the Product....... 18
Correlation to Mathematics Standards..... 19
Leveled Texts......... 21
Collecting Data...... 21
Creating Pictographs...... 29
Analyzing Pictographs...... 37
Creating Bar Graphs...... 45
Analyzing Bar Graphs..... 53
Creating Line Graphs...... 61
Analyzing Line Graphs....... 69
Creating Circle Graphs...... 77
Analyzing Circle Graphs...... 85
Comparing Graphs.......... 93
What Does Mean Mean?....... 101
Median in the Middle...... 109
Mode and Range.......... 117
Probability of Events....... 125
Probability Experiments..... 133
Appendices...... 141
References Cited......... 141
Contents of Teacher Resource CD...... 142

How Numbers Rule the World: The Use and Abuse of Statistics in Global Politics

Lorenzo Fioramonti 

Zed Books | 2014 | 281 páginas | rar - pdf | Mb

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Numbers dominate global politics and as a result our everyday lives. Credit ratings steer financial markets and can make or break the future of entire nations. GDP drives our economies. Stock market indices flood our media and national debates. Statistical calculations define how we deal with climate change, poverty and sustainability. But what is behind these numbers? By what processes are they created? In How Numbers Rule the World Lorenzo Fioramonti reveals the hidden agendas underpinning the use of statistics and those who control them. Most worryingly, he shows how numbers have been used as a means to reinforce the grip of markets on our social and political life, curtailing public participation and rational debate.
An innovative and timely exposé of the politics, power and contestation of numbers.


Contents
acknowledgements vi
introduction The politics of statistics 1
chapter 1 The power of numbers 10
chapter 2 New global rulers: the untameable power of credit rating 39
chapter 3 Fiddling while the planet burns: the marketization of climate change 68
chapter 4 Measuring the unmeasurable: the financialization of nature 104
chapter 5 Numbers for good? The quest for aid effectiveness and social impact 144
conclusion Rethinking numbers, rethinking governance 192
notes 214
bibliography 246

index 261

The Visual Organization: Data Visualization, Big Data, and the Quest for Better Decisions

Phil Simon

Wiley | 2014 | 236 páginas | rar - pdf | 18,43 Mb

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The era of Big Data has arrived but, on many levels, most organizations are woefully unprepared. Far too many enterprises erroneously believe and act like nothing has really changed. As such, they continue to depend exclusively on reporting stalwarts like Microsoft Excel, static dashboards, basic query applications, and even traditional business intelligence tools. And they are missing out on tremendous opportunities. 
Amidst all of the hype and confusion surrounding Big Data, though, a new type of enterprise is emerging: The Visual Organization. A relative handful of organizations has realized that today's ever-increasing data streams, volumes, and velocity require new applications. In turn, these new tools promote a different mind-set--one based upon data discovery and exploration, not conventional enterprise "reporting." For instance, Netflix builds cutting-edge dataviz tools to better understand its 40 million customers. And it's hardly alone in its innovative use of new data visualization technologies. Employees at Autodesk use a remarkable and interactive tool that visualizes current and historical employee movement. From this, they can identify potential management issues and see what a corporate reorg really looks like. Through cutting-edge dataviz, startup Wedgies instantly serves up real-time poll results while monitoring poll traction and site issues. The University of Texas is bringing a visual type of transparency to academia. It makes unprecedented amounts and sources of institutional data available on its website. Anyone with the desire and an Internet connection can slice and dice UT data in myriad ways. And then there's eBay. Powerful data-discovery tools allow employees to effectively "see" what ebay.com would look like as a brick-and-mortar store. In The Visual Organization, award-winning author, keynote speaker, and recognized technology expert Phil Simon demonstrates how progressive enterprises have turned traditional dataviz on its head. In their stead, they are embracing new, interactive, and more robust tools that help locate the signals in the noise that is Big Data. As a result, these enterprises are asking better questions and making better business decisions. Rife with real-world examples and practical advice, The Visual Organization is a full-color tour de force. Simon deftly explains how organizations can do more than just survive the data deluge; they can thrive in it. It is required reading for executives, professionals, and others interested in unleashing the power of their data.

Statistics and Probability with Applications for Engineers and Scientists

Bhisham C. Gupta e Irwin Guttman 

Wiley | 2013 | 898 páginas | rar - pdf | 9,18 Mb

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An understanding of statistical tools is essential for engineers and scientists who often need to deal with data analysis over the course of their work. Statistics and Probability with Applications for Engineers and Scientists walks readers through a wide range of popular statistical techniques, explaining step-by-step how to generate, analyze, and interpret data for diverse applications in engineering and the natural sciences.

Unique among books of this kind, Statistics and Probability with Applications for Engineers and Scientists covers descriptive statistics first, then goes on to discuss the fundamentals of probability theory. Along with case studies, examples, and real-world data sets, the book incorporates clear instructions on how to use the statistical packages Minitab® and Microsoft® Office Excel® to analyze various data sets. The book also features:

• Detailed discussions on sampling distributions, statistical estimation of population parameters, hypothesis testing, reliability theory, statistical quality control including Phase I and Phase II control charts, and process capability indices

• A clear presentation of nonparametric methods and simple and multiple linear regression methods, as well as a brief discussion on logistic regression method
• Comprehensive guidance on the design of experiments, including randomized block designs, one- and two-way layout designs, Latin square designs, random effects and mixed effects models, factorial and fractional factorial designs, and response surface methodology
• A companion website containing data sets for Minitab and Microsoft Office Excel, as well as JMP ® routines and results

Assuming no background in probability and statistics, Statistics and Probability with Applications for Engineers and Scientists features a unique, yet tried-and-true, approach that is ideal for all undergraduate students as well as statistical practitioners who analyze and illustrate real-world data in engineering and the natural sciences.

Elementary Statistics: Picturing the World

Ron Larson e Betsy Farber

Pearson | 2014 - 6ª edição |705 páginas | rar - pdf |12,4 Mb

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5.ª edição - 2012

Statistics opens a window to the modern world, and this market-leading text makes it easy to understand! Larson and Farber’s Elementary Statistics: Picturing the World, Sixth Edition, provides stepped out instruction, real-life examples and exercises, and the use of technology to offer the most accessible approach. The authors carefully develop theory through strong pedagogy, and examples show how statistics is used to picture and describe the world. In keeping with the premise that students learn best by doing, it includes more than 210 examples and more than 2300 exercises, to make the concepts of statistics a part of students’ everyday lives.

Contents

PART ONE. DESCRIPTIVE STATISTICS

1. Introduction to Statistics

1.1. An Overview of Statistics

1.2. Data Classification

            Case Study: Rating Television Shows in the

            United States

1.3. Data Collection and Experimental Design

            Activity: Random Numbers

            Uses and Abuses

Chapter Summary

Review Exercises

Chapter Quiz

Chapter Test

            Real Statistics-Real Decisions-Putting It All Together

            History of Statistics-Timeline

            Technology: Using Technology in Statistics

2. Descriptive Statistics

2.1. Frequency Distributions and Their Graphs

2.2. More Graphs and Displays

2.3. Measures of Central Tendency

            Activity: Mean Versus Median

2.4. Measures of Variation

            Activity: Standard Deviation

            Case Study: Business Size

2.5. Measures of Position

            Uses and Abuses

Chapter Summary

Review Exercises

Chapter Quiz

Chapter Test

            Real Statistics-Real Decisions-Putting It All Together

            Technology: Parking Tickets

            Using Technology to Determine Descriptive

            Statistics

Cumulative Review: Chapters 1 and 2

PART TWO. PROBABILITY & PROBABILITY DISTRIBUTIONS

3. Probability

3.1. Basic Concepts of Probability and Counting

            Activity: Simulating the Stock Market

3.2. Conditional Probability and the Multiplication Rule

3.3. The Addition Rule

            Activity: Simulating the Probability of Rolling a 3 or 4

            Case Study: United States Congress

3.4. Additional Topics in Probability and Counting

            Uses and Abuses

Chapter Summary

Review Exercises

Chapter Quiz

Chapter Test

            Real Statistics-Real Decisions-Putting It All Together

            Technology: Simulation: Composing Mozart

            Variations with Dice

4. Discrete Probability Distributions

4.1. Probability Distributions

4.2. Binomial Distributions

            Activity: Binomial Distribution

            Case Study: Distribution of Number of Hits in

            Baseball Games

4.3. More Discrete Probability Distributions

            Uses and Abuses

Chapter Summary

Review Exercises

Chapter Quiz

Chapter Test

            Real Statistics-Real Decisions-Putting It All Together

            Technology: Simulation: Using Poisson

            Distributions as Queuing Models

5. Normal Probability Distributions

5.1. Introduction to Normal Distributions and the Standard Normal Distribution

5.2. Normal Distributions: Finding Probabilities

5.3. Normal Distributions: Finding Values

            Case Study: Birth Rates in America

5.4. Sampling Distributions and the Central Limit Theorem

            Activity: Sampling Distributions

5.5. Normal Approximations to Binomial Distributions

            Uses and Abuses

Chapter Summary

Review Exercises

Chapter Quiz

Chapter Test

            Real Statistics-Real Decisions-Putting It All Together

            Technology: Simulation: Age Distribution in the

            United States

Cumulative Review: Chapters 3 to 5

PART THREE. STATISTICAL INFERENCE

6. Confidence Intervals

6.1. Confidence Intervals for the Mean (¡ Known)

6.2. Confidence Intervals for the Mean (¡ Unknown)

            Activity: Confidence Intervals for a Mean

            Case Study: Marathon Training

6.3. Confidence Intervals for Population Proportions

            Activity: Confidence Intervals for a Proportion

6.4. Confidence Intervals for Variance and Standard Deviation

            Uses and Abuses

Chapter Summary

Review Exercises

Chapter Quiz

Chapter Test

            Real Statistics-Real Decisions-Putting It All Together

            Technology: Simulation: Most Admired Polls

            Using Technology to Construct Confidence

            Intervals

7. Hypothesis Testing with One Sample

7.1. Introduction to Hypothesis Testing

7.2. Hypothesis Testing for the Mean (¡ Known)

7.3. Hypothesis Testing for the Mean (¡ Unknown)

            Activity: Hypothesis Test for a Mean

            Case Study: Human Body Temperature: What's

            Normal?

7.4. Hypothesis Testing for Proportions

            Activity: Hypothesis Test for a Proportion

7.5. Hypothesis Testing for Variance and Standard Deviation

A Summary of Hypothesis Testing

            Uses and Abuses

Chapter Summary

Review Exercises

Chapter Quiz

Chapter Test

            Real Statistics-Real Decisions-Putting It All Together

            Technology: The Case of the Vanishing Women

            Using Technology to Perform Hypothesis Tests

8. Hypothesis Testing with Two Samples

8.1. Testing the Difference Between Means (Independent Samples, ¡₁ and ¡₂ Known)

8.2. Testing the Difference Between Means (Independent Samples, ¡₁ and ¡₂ Unknown)

8.3. Testing the Difference Between Means (Dependent Samples)

8.4. Testing the Difference Between Proportions

A Summary of Hypothesis Testing

            Uses and Abuses

Chapter Summary

Review Exercises

Chapter Quiz

Chapter Test

            Real Statistics-Real Decisions-Putting It All Together

            Technology: Tails over Heads

            Using Technology to Perform Two-Sample

            Hypothesis Tests

Cumulative Review: Chapters 6 to 8

PART FOUR. MORE STATISTICAL INFERENCE

9. Correlation and Regression

9.1 Correlation

            Activity: Correlation by Eye

9.2. Linear Regression

            Activity: Regression by Eye

            Case Study: Correlation by Body Measurements

9.3. Measures of Regression and Prediction Intervals

9.4. Multiple Regression

A Summary of Hypothesis Testing

            Uses and Abuses

Chapter Summary

Review Exercises

Chapter Quiz

Chapter Test

            Real Statistics-Real Decisions-Putting It All Together

            Technology: Nutrients in Breakfast Cereals

10. Chi-Square Tests and the F-Distribution

10.1. Goodness-of-Fit Test

10.2. Independence

            Case Study: Food Safety Survey

10.3. Comparing Two Variances

10.4. Analysis of Variance

            Uses and Abuses

Chapter Summary

Review Exercises

Chapter Quiz

Chapter Test

            Real Statistics-Real Decisions-Putting It All Together

            Technology: Teacher Salaries

Cumulative Review: Chapters 9 and 10