W.H. Freeman is excited to be publishing a new text by David Moore: Essential Statistics.

David Moore’s considerable experience as a statistician and instructor, and his commitment to producing high-quality, innovative introductory statistics textbooks motivated him to create Essential Statistics. The text offers the same highly successful approach and pedagogy of David Moore’s bestselling The Basic Practice of Statistics (BPS), Fifth Edition, but in a briefer, more concise format. Through careful rewriting, he has shortened and simplified explanations, to better highlight the key, essential, statistical ideas and methods students need to know.

The text is based on three principles: balanced content, the importance of ideas, and experience with data. Using a “just the basics” approach, the text clarifies and simplifies important concepts and methods, while engaging students with contemporary, realistic examples. Throughout the book, exercises help students check and apply their skills. A four-step problem-solving process in examples and exercises encourage good habits that go beyond graphs and calculations to ask, “What do the data tell me?”

Essential Statistics is what its name suggests: a basic introduction to statistical ideas and methods that aims to equip students to carry out common statistical procedures and to follow statistical reasoning in their fields of study and in their future employment.

David S. Moore is Shanti S. Gupta Distinguished Professor of Statistics, Emeritus, at Purdue University and was 1998 president of the American Statistical Association. He received his A.B. from Princeton and his Ph.D. from Cornell, both in mathematics. He has written many research papers in statistical theory and served on the editorial boards of several major journals. Professor Moore is an elected fellow of the American Statistical Association and of the Institute of Mathematical Statistics and an elected member of the International Statistical Institute. He has served as program director for statistics and probability at the National Science Foundation.

In recent years, Professor Moore has devoted his attention to the teaching of statistics. He was the content developer for the Annenberg/Corporation for Public Broadcasting college-level telecourse Against All Odds: Inside Statistics and for the series of video modules Statistics: Decisions through Data, intended to aid the teaching of statistics in schools. He is the author of influential articles on statistics education and of several leading texts. Professor Moore has served as president of the International Association for Statistical Education and has received the Mathematical Association of America’s national award for distinguished college or university teaching of mathematics.

CHAPTER 1 Picturing Distributions with Graphs 3
Individuals and variables / 3
Categorical variables: pie charts and bar graphs / 5
Quantitative variables: histograms / 10
Interpreting histograms / 12
Quantitative variables: stemplots / 16
Time plots / 19

CHAPTER 2 Describing Distributions with Numbers 29
Measuring center: the mean / 29
Measuring center: the median / 31
Comparing the mean and the median / 32
Measuring spread: the quartiles / 33
The five-number summary and boxplots / 34
Measuring spread: the standard deviation / 37
Choosing measures of center and spread / 39
Using technology / 40
Organizing a statistical problem / 40

CHAPTER 3 The Normal Distributions 51
Density curves / 51
Describing density curves / 54
Normal distributions / 55
The 68-95-99.7 rule / 57
The standard Normal distribution / 59
Finding Normal proportions / 61
Using the standard Normal table / 62
Finding a value given a proportion / 65

CHAPTER 4 Scatterplots and Correlation 73
Explanatory and response variables / 73
Displaying relationships: scatterplots / 74
Interpreting scatterplots / 76
Measuring linear association: correlation / 79
Facts about correlation / 80

CHAPTER 5 Regression 91
Regression lines / 91
The least-squares regression line / 94
Using technology / 95
Facts about least-squares regression / 97
Residuals / 98
Influential observations / 101
Cautions about correlation and regression / 103
Association does not imply causation / 105

CHAPTER 6 Exploring Data: Part I Review 115
Part I Summary / 115
Review Exercises / 116
Supplementary Exercises / 121

PART II: From Exploration to Inference | 127

CHAPTER 7 Producing Data: Sampling 129
Population versus sample / 129
How to sample badly / 131
Simple random samples / 132
Inference about the population / 136
Cautions about sample surveys / 137

CHAPTER 8 Producing Data: Experiments 145
Observation versus experiment / 145
Subjects, factors, treatments / 147
How to experiment badly / 149
Randomized comparative experiments / 150
The logic of randomized comparative experiments / 153
Cautions about experimentation / 154
Matched pairs designs / 156

CHAPTER 9 Introducing Probability 163
The idea of probability / 164
Probability models / 166
Probability rules / 168
Discrete probability models / 171
Continuous probability models / 172
Random variables / 176

iv * Starred material is not required for later parts of the text.

CHAPTER 10 Sampling Distributions 183
Parameters and statistics / 183
Statistical estimation and the law of large numbers / 184
Sampling distributions / 187
The mean and standard deviation of ¯x / 189
The central limit theorem / 190

CHAPTER 11 General Rules of Probability* 199
Independence and the multiplication rule / 199
The general addition rule / 203
Conditional probability / 205
The general multiplication rule / 20
Tree diagrams / 208

CHAPTER 12 Binomial Distributions* 217
The binomial setting and binomial distributions / 217
Binomial distributions in statistical sampling / 218
Binomial probabilities / 219
Binomial mean and standard deviation / 221
The Normal approximation to binomial distributions / 223

CHAPTER 13 Introduction to Inference 231
The reasoning of statistical estimation / 232
Confidence intervals for a population mean / 235
The reasoning of statistical tests / 238
Stating hypotheses / 241 P-values / 242
Tests for a population mean / 245
Statistical significance / 248

CHAPTER 14 Thinking about Inference 257
Conditions for inference in practice / 257
How confidence intervals behave / 261
Sample size for confidence intervals / 263
How significance tests behave / 264

CHAPTER 15 From Exploration to Inference: Part II Review 273
Part II Summary / 273
Review Exercises / 275
Supplementary Exercises / 279
Optional Exercises / 281

PART III: Inference about Variables | 283

CHAPTER 16 Inference about a Population Mean 285
Conditions for inference about a mean / 285
The t distributions / 286
The one-sample t confidence interval / 288
The one-sample t test / 291
Using technology / 293
Matched pairs t procedures / 295
Robustness of t procedures / 297

CHAPTER 17 Two-Sample Problems 307
Comparing two population means / 308
Two-sample t procedures / 310
Using technology / 315
Robustness again / 317

CHAPTER 18 Inference about a Population Proportion 327
The sample proportion ˆp / 328
Large-sample confidence intervals for a proportion / 330
Choosing the sample size / 332
Significance tests for a proportion / 334

CHAPTER 19 Comparing Two Proportions 341
Two-sample problems: proportions / 341
The sampling distribution of a difference between proportions / 342
Large-sample confidence intervals form comparing proportions / 343
Using technology / 344
Significance tests for comparing proportions / 346

CHAPTER 20 Inference about Variables: Part III Review 353
Statistics in Outline / 353
Part III Summary / 354
Review Exercises / 356
Supplementary Exercises / 359

PART IV: Inference about Relationships | 363

CHAPTER 21 Two Categorical Variables: The Chi-Square Test 365
Two-way tables / 365
Is there a relationship? Expected cell counts / 370
The chi-square test / 372
Data analysis for chi-square / 374
Another use of the chi-square test / 378
The chi-square distributions / 380
The chi-square test for goodness of fit / 382

CHAPTER 22 Inference for Regression 393
Conditions for regression inference / 395
Estimating the parameters / 396
Using technology / 399
Testing the hypothesis of no linear relationship / 401
Testing lack of correlation / 403
Confidence intervals for the regression slope / 404
Inference about prediction / 405
Checking the conditions for inference / 408

CHAPTER 23 One-Way Analysis of Variance:
Comparing Several Means 421
The analysis of variance F test / 423
Using technology / 425
The idea of analysis of variance / 429
Conditions for ANOVA / 431 F distributions and degrees of freedom / 435

NOTES AND DATA SOURCES / 445

TABLES / 463

TABLE A Standard Normal Probabilities / 464

TABLE B Random Digits / 466

TABLE C t Distribution Critical Values / 467

TABLE D Chi-Square Distribution Critical Values / 468

ANSWERS TO SELECTED EXERCISES / 469

INDEX / 495

Additional Material (available on the Essential Statistics CD and Web site whfreeman.com/essentialstats)

CHAPTER 24 Nonparametric Tests
Comparing two samples: the Wilcoxon rank sum test
The Normal approximation for W Using technology
What hypotheses does Wilcoxon test?
Dealing with ties in rank tests
Matched pairs: the Wilcoxon signed rank test
The Normal approximation for W+
Dealing with ties in the signed rank test
Commentary: Data Ethics
Applets for Interactive Learning

Our reader reviews allow you to share your comments on titles you liked,
or didn't, with others. By submitting an online review, you are representing to
Barnes & Noble.com that all information contained in your review is original
and accurate in all respects, and that the submission of such content by you
and the posting of such content by Barnes & Noble.com does not and will not
violate the rights of any third party. Please follow the rules below to help
ensure that your review can be posted.

Reviews by Our Customers Under the Age of 13

We highly value and respect everyone's opinion concerning the titles we offer.
However, we cannot allow persons under the age of 13 to have accounts at BN.com or
to post customer reviews. Please see our Terms of Use for more details.

What to exclude from your review:

Please do not write about reviews, commentary, or information posted on the product page. If you see any errors in the
information on the product page, please send us an email.

Reviews should not contain any of the following:

- HTML tags, profanity, obscenities, vulgarities, or comments that defame anyone

- Time-sensitive information such as tour dates, signings, lectures, etc.

- Single-word reviews. Other people will read your review to discover why you liked or didn't like the title. Be descriptive.

- Comments focusing on the author or that may ruin the ending for others

- Phone numbers, addresses, URLs

- Pricing and availability information or alternative ordering information

- Advertisements or commercial solicitation

Reminder:

- By submitting a review, you grant to Barnes & Noble.com and its
sublicensees the royalty-free, perpetual, irrevocable right and license to use the
review in accordance with the Barnes & Noble.com Terms of Use.

- Barnes & Noble.com reserves the right not to post any review -- particularly
those that do not follow the terms and conditions of these Rules. Barnes & Noble.com
also reserves the right to remove any review at any time without notice.

- See Terms of Use for other conditions and disclaimers.

Search for Products You'd Like to Recommend

Create a Pen Name

Welcome, penname

You have successfully created your Pen Name. Start enjoying the benefits of the BN.com Community today.

If you find inappropriate content, please report it to Barnes & Noble

## More About This Textbook

## Overview

W.H. Freeman is excited to be publishing a new text by David Moore:

.Essential StatisticsDavid Moore’s considerable experience as a statistician and instructor, and his commitment to producing high-quality, innovative introductory statistics textbooks motivated him to create

Essential Statistics.The text offers the same highly successful approach and pedagogy of David Moore’s bestsellingThe Basic Practice of Statistics(BPS), Fifth Edition, but in a briefer, more concise format. Through careful rewriting, he has shortened and simplified explanations, to better highlight the key,essential, statistical ideas and methods students need to know.The text is based on three principles: balanced content, the importance of ideas, and experience with data. Using a “just the basics” approach, the text clarifies and simplifies important concepts and methods, while engaging students with contemporary, realistic examples. Throughout the book, exercises help students check and apply their skills. A four-step problem-solving process in examples and exercises encourage good habits that go beyond graphs and calculations to ask, “What do the data tell me?”

Essential Statisticsis what its name suggests: a basic introduction to statistical ideas and methods that aims to equip students to carry out common statistical procedures and to follow statistical reasoning in their fields of study and in their future employment.## Product Details

## Related Subjects

## Meet the Author

David S. Moore is Shanti S. Gupta Distinguished Professor of Statistics, Emeritus, at Purdue University and was 1998 president of the American Statistical Association. He received his A.B. from Princeton and his Ph.D. from Cornell, both in mathematics. He has written many research papers in statistical theory and served on the editorial boards of several major journals. Professor Moore is an elected fellow of the American Statistical Association and of the Institute of Mathematical Statistics and an elected member of the International Statistical Institute. He has served as program director for statistics and probability at the National Science Foundation.

In recent years, Professor Moore has devoted his attention to the teaching of statistics. He was the content developer for the Annenberg/Corporation for Public Broadcasting college-level telecourse

Against All Odds: Inside Statisticsand for the series of video modulesStatistics: Decisions through Data, intended to aid the teaching of statistics in schools. He is the author of influential articles on statistics education and of several leading texts. Professor Moore has served as president of the International Association for Statistical Education and has received the Mathematical Association of America’s national award for distinguished college or university teaching of mathematics.## Table of Contents

PART I:Exploring Data | 1CHAPTER 1Picturing Distributions with Graphs 3Individuals and variables / 3

Categorical variables: pie charts and bar graphs / 5

Quantitative variables: histograms / 10

Interpreting histograms / 12

Quantitative variables: stemplots / 16

Time plots / 19

CHAPTER 2 Describing Distributions with Numbers 29Measuring center: the mean / 29

Measuring center: the median / 31

Comparing the mean and the median / 32

Measuring spread: the quartiles / 33

The five-number summary and boxplots / 34

Measuring spread: the standard deviation / 37

Choosing measures of center and spread / 39

Using technology / 40

Organizing a statistical problem / 40

CHAPTER 3The Normal Distributions 51Density curves / 51

Describing density curves / 54

Normal distributions / 55

The 68-95-99.7 rule / 57

The standard Normal distribution / 59

Finding Normal proportions / 61

Using the standard Normal table / 62

Finding a value given a proportion / 65

CHAPTER 4Scatterplots and Correlation 73Explanatory and response variables / 73

Displaying relationships: scatterplots / 74

Interpreting scatterplots / 76

Measuring linear association: correlation / 79

Facts about correlation / 80

CHAPTER 5Regression 91Regression lines / 91

The least-squares regression line / 94

Using technology / 95

Facts about least-squares regression / 97

Residuals / 98

Influential observations / 101

Cautions about correlation and regression / 103

Association does not imply causation / 105

CHAPTER 6Exploring Data: Part I Review 115Part I Summary / 115

Review Exercises / 116

Supplementary Exercises / 121

PART II:From Exploration to Inference | 127CHAPTER 7Producing Data: Sampling 129Population versus sample / 129

How to sample badly / 131

Simple random samples / 132

Inference about the population / 136

Cautions about sample surveys / 137

CHAPTER 8Producing Data: Experiments 145Observation versus experiment / 145

Subjects, factors, treatments / 147

How to experiment badly / 149

Randomized comparative experiments / 150

The logic of randomized comparative experiments / 153

Cautions about experimentation / 154

Matched pairs designs / 156

CHAPTER 9Introducing Probability 163The idea of probability / 164

Probability models / 166

Probability rules / 168

Discrete probability models / 171

Continuous probability models / 172

Random variables / 176

iv

* Starred material is not required for later parts of the text.CHAPTER 10Sampling Distributions 183Parameters and statistics / 183

Statistical estimation and the law of large numbers / 184

Sampling distributions / 187

The mean and standard deviation of ¯

x/ 189The central limit theorem / 190

CHAPTER 11General Rules of Probability* 199Independence and the multiplication rule / 199

The general addition rule / 203

Conditional probability / 205

The general multiplication rule / 20

Tree diagrams / 208

CHAPTER 12Binomial Distributions* 217The binomial setting and binomial distributions / 217

Binomial distributions in statistical sampling / 218

Binomial probabilities / 219

Binomial mean and standard deviation / 221

The Normal approximation to binomial distributions / 223

CHAPTER 13Introduction to Inference 231The reasoning of statistical estimation / 232

Confidence intervals for a population mean / 235

The reasoning of statistical tests / 238

Stating hypotheses / 241

P-values / 242Tests for a population mean / 245

Statistical significance / 248

CHAPTER 14Thinking about Inference 257Conditions for inference in practice / 257

How confidence intervals behave / 261

Sample size for confidence intervals / 263

How significance tests behave / 264

CHAPTER 15From Exploration to Inference: Part II Review 273Part II Summary / 273

Review Exercises / 275

Supplementary Exercises / 279

Optional Exercises / 281

PART III:Inference about Variables | 283CHAPTER 16Inference about a Population Mean 285Conditions for inference about a mean / 285

The

tdistributions / 286The one-sample

tconfidence interval / 288The one-sample

ttest / 291Using technology / 293

Matched pairs

tprocedures / 295Robustness of

tprocedures / 297CHAPTER 17Two-Sample Problems 307Comparing two population means / 308

Two-sample

tprocedures / 310Using technology / 315

Robustness again / 317

CHAPTER 18Inference about a Population Proportion 327The sample proportion ˆ

p/ 328Large-sample confidence intervals for a proportion / 330

Choosing the sample size / 332

Significance tests for a proportion / 334

CHAPTER 19Comparing Two Proportions 341Two-sample problems: proportions / 341

The sampling distribution of a difference between proportions / 342

Large-sample confidence intervals form comparing proportions / 343

Using technology / 344

Significance tests for comparing proportions / 346

CHAPTER 20Inference about Variables: Part III Review 353Statistics in Outline / 353

Part III Summary / 354

Review Exercises / 356

Supplementary Exercises / 359

PART IV:Inference about Relationships | 363CHAPTER 21Two Categorical Variables: The Chi-Square Test 365Two-way tables / 365

Is there a relationship? Expected cell counts / 370

The chi-square test / 372

Data analysis for chi-square / 374

Another use of the chi-square test / 378

The chi-square distributions / 380

The chi-square test for goodness of fit / 382

CHAPTER 22Inference for Regression 393Conditions for regression inference / 395

Estimating the parameters / 396

Using technology / 399

Testing the hypothesis of no linear relationship / 401

Testing lack of correlation / 403

Confidence intervals for the regression slope / 404

Inference about prediction / 405

Checking the conditions for inference / 408

CHAPTER 23One-Way Analysis of Variance:Comparing Several Means 421

The analysis of variance

Ftest / 423Using technology / 425

The idea of analysis of variance / 429

Conditions for ANOVA / 431

Fdistributions and degrees of freedom / 435NOTES AND DATA SOURCES/ 445TABLES/ 463TABLE A Standard Normal Probabilities / 464

TABLE B Random Digits / 466

TABLE C

tDistribution Critical Values / 467TABLE D Chi-Square Distribution Critical Values / 468

ANSWERS TO SELECTED EXERCISES/ 469INDEX / 495Additional Material (available on the

Essential StatisticsCD and Web site whfreeman.com/essentialstats)CHAPTER 24Nonparametric TestsComparing two samples: the Wilcoxon rank sum test

The Normal approximation for

W

Using technologyWhat hypotheses does Wilcoxon test?

Dealing with ties in rank tests

Matched pairs: the Wilcoxon signed rank test

The Normal approximation for

W+Dealing with ties in the signed rank test

Commentary: Data Ethics

Applets for Interactive Learning