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Introduction to the Practice of Statistics w/CD-ROM

by: Moore, David S.; McCabe, George

Introduction to the Practice of Statistics w/CD-ROM

by: Moore, David S.; McCabe, George

ISBN 13:
9780716764007
ISBN 10:
0716764008
Edition: 5th
Format: Display
Copyright: 02/01/2005
Publisher: W. H. Freeman

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Summary

With its focus on data analysis, statistical reasoning, and the way statisticians actually work, Introduction to the Practice of Statistics (IPS) helped bring the power of critical thinking and practical applications to today's statistics classroom. Unlike more traditional ?plug and chug? /formula driven texts, IPS de-emphasizes probability and gives students a deeper understanding of statistics.

To Teachers: About This Book

xiii

To Students: What Is Statistics?

xxxi

About the Authors

xxxv

PART 1 Looking at Data

(250)

Looking at Data---Distributions

(98)

Introduction

(3)

Variables

(2)

Measurement: know your variables

(1)

Displaying Distributions with Graphs

(33)

Graphs for categorical variables

(2)

Data analysis in action: don't hang up on me

(2)

Stemplots

(3)

Histograms

(3)

Examining distributions

(1)

Dealing with outliers

(1)

Time plots

(2)

Beyond the basics: decomposing time series

(2)

Section 1.1 Summary

(2)

Section 1.1 Exercises

(15)

Describing Distributions with Numbers

(24)

Measuring center: the mean

(2)

Measuring center: the median

(1)

Mean versus median

(1)

Measuring spread: the quartiles

(2)

The five-number summary and boxplots

(1)

The 1.5 x IQR rule for suspected outliers

(2)

Measuring spread: the standard deviation

(2)

Properties of the standard deviation

(1)

Choosing measures of center and spread

(1)

Changing the unit of measurement

(2)

Section 1.2 Summary

(1)

Section 1.2 Exercises

(8)

Density Curves and Normal Distributions

(37)

Density curves

(3)

Measuring center and spread for density curves

(1)

Normal distributions

(2)

The 68--95--99.7 rule

(2)

Standardizing observations

(1)

Normal distribution calculations

(2)

Using the standard normal table

(2)

Inverse normal calculations

(2)

Normal quantile plots

(3)

Beyond the basics: density estimation

(1)

Section 1.3 Summary

(1)

Section 1.3 Exercises

(10)

Chapter 1 Exercises

(5)

EESEE Case Studies

(2)

Looking at Data---Relationships

101

(90)

Introduction

102

(2)

Examining relationships

102

(2)

Scatterplots

104

(19)

Interpreting scatterplots

105

(1)

Adding categorical variables to scatterplots

106

(1)

More examples of scatterplots

107

(3)

Beyond the basics: scatterplot smoothers

110

(1)

Categorical explanatory variables

111

(1)

Section 2.1 Summary

112

(1)

Section 2.1 Exercises

112

(11)

Correlation

123

(9)

The correlation r

124

(1)

Properties of correlation

124

(3)

Section 2.2 Summary

127

(1)

Section 2.2 Exercises

127

(5)

Least-Squares Regression

132

(19)

Fitting a line to data

133

(1)

Prediction

134

(1)

Least-squares regression

135

(3)

Interpreting the regression line

138

(1)

Correlation and regression

138

(4)

Understanding r2

142

(1)

Beyond the basics: transforming relationships

143

(2)

Section 2.3 Summary

145

(1)

Section 2.3 Exercises

145

(6)

Cautions about Correlation and Regression

151

(22)

Residuals

151

(3)

Outliers and influential observations

154

(4)

Beware the lurking variable

158

(3)

Beware correlations based on averaged data

161

(1)

The restricted-range problem

161

(1)

Beyond the basics: data mining

162

(1)

Section 2.4 Summary

163

(1)

Section 2.4 Exercises

163

(10)

The Question of Causation

173

(18)

Explaining association: causation

174

(1)

Explaining association: common response

175

(1)

Explaining association: confounding

176

(1)

Establishing causation

177

(1)

Section 2.5 Summary

178

(1)

Section 2.5 Exercises

179

(2)

Chapter 2 Exercises

181

(7)

EESEE Case Studies

188

(3)

Producing Data

191

(60)

Introduction

192

(1)

First Steps

192

(6)

Where to find data: the library and the Internet

193

(1)

Sampling

194

(1)

Experiments

195

(1)

Section 3.1 Summary

196

(1)

Section 3.1 Exercises

197

(1)

Design of Experiments

198

(20)

Comparative experiments

200

(1)

Randomization

201

(1)

Randomized comparative experiments

202

(1)

How to randomize

203

(3)

Cautions about experimentation

206

(1)

Matched pairs designs

207

(1)

Block designs

208

(1)

Section 3.2 Summary

209

(1)

Section 3.2 Exercises

210

(8)

Sampling Design

218

(13)

Simple random samples

219

(1)

Stratified samples

220

(1)

Multistage samples

221

(1)

Cautions about sample surveys

222

(2)

Section 3.3 Summary

224

(1)

Section 3.3 Exercises

225

(6)

Toward Statistical Inference

231

(20)

Sampling variability

232

(1)

Sampling distributions

233

(3)

Bias and variability

236

(2)

Sampling from large populations

238

(1)

Why randomize?

238

(1)

Beyond the basics: capture-recapture sampling

239

(1)

Section 3.4 Summary

240

(1)

Section 3.4 Exercises

240

(6)

Chapter 3 Exercises

246

(3)

EESEE Case Studies

249

(2)

PART 2 Probability and Inference

251

(328)

Probability: The Study of Randomness

253

(80)

Introduction

254

(1)

Randomness

254

(5)

The language of probability

255

(1)

Thinking about randomness

256

(1)

The uses of probability

256

(1)

Section 4.1 Summary

257

(1)

Section 4.1 Exercises

257

(2)

Probability Models

259

(18)

Sample spaces

259

(2)

Intuitive probability

261

(1)

Probability rules

262

(2)

Assigning probabilities: finite number of outcomes

264

(1)

Assigning probabilities: equally likely outcomes

265

(1)

Independence and the multiplication rule

266

(3)

Applying the probability rules

269

(1)

Section 4.2 Summary

270

(1)

Section 4.2 Exercises

271

(6)

Random Variables

277

(14)

Discrete random variables

278

(4)

Continuous random variables

282

(2)

Normal distributions as probability distributions

284

(2)

Section 4.3 Summary

286

(1)

Section 4.3 Exercises

286

(5)

Means and Variances of Random Variables

291

(20)

The mean of a random variable

291

(3)

Statistical estimation and the law of large numbers

294

(2)

Thinking about the law of large numbers

296

(1)

Beyond the basics: more laws of large numbers

297

(1)

Rules for means

298

(2)

The variance of a random variable

300

(1)

Rules for variances

301

(3)

Section 4.4 Summary

304

(1)

Section 4.4 Exercises

305

(6)

General Probability Rules

311

(22)

General addition rules

312

(3)

Conditional probability

315

(4)

General multiplication rules

319

(1)

Tree diagrams

320

(1)

Bayes's rule

321

(1)

Independence again

322

(1)

Section 4.5 Summary

323

(1)

Section 4.5 Exercises

323

(5)

Chapter 4 Exercises

328

(3)

EESEE Case Studies

331

(2)

Sampling Distributions

333

(48)

Introduction

334

(1)

Sampling Distributions for Counts and Proportions

335

(23)

The binomial distributions for sample counts

335

(1)

Binomial distributions in statistical sampling

336

(1)

Finding binomial probabilities: software and tables

337

(3)

Binomial mean and standard deviation

340

(1)

Sample proportions

341

(2)

Normal approximation for counts and proportions

343

(4)

The continuity correction

347

(1)

Binomial formulas

348

(2)

Section 5.1 Summary

350

(1)

Section 5.1 Exercises

351

(7)

The Sampling Distribution of a Sample Mean

358

(23)

The mean and standard deviation of x

360

(2)

The central limit theorem

362

(3)

A few more facts

365

(2)

Beyond the basics: Weibull distributions

367

(1)

Section 5.2 Summary

368

(1)

Section 5.2 Exercises

369

(6)

Chapter 5 Exercises

375

(3)

EESEE Case Studies

378

(3)

Introduction to Inference

381

(68)

Introduction

382

(1)

Estimating with Confidence

383

(17)

Statistical confidence

384

(1)

Confidence intervals

385

(2)

Confidence interval for a population mean

387

(3)

How confidence intervals behave

390

(1)

Choosing the sample size

391

(2)

Some cautions

393

(1)

Beyond the basics: the bootstrap

394

(1)

Section 6.1 Summary

395

(1)

Section 6.1 Exercises

396

(4)

Tests of Significance

400

(24)

The reasoning of significance tests

400

(2)

Stating hypotheses

402

(1)

Test statistics

403

(1)

P-values

404

(2)

Statistical significance

406

(3)

Tests for a population mean

409

(4)

Two-sided significance tests and confidence intervals

413

(2)

P-values versus fixed α

415

(1)

Section 6.2 Summary

416

(1)

Section 6.2 Exercises

416

(8)

Use and Abuse of Tests

424

(6)

Choosing a level of significance

424

(1)

What statistical significance does not mean

425

(1)

Don't ignore lack of significance

425

(1)

Statistical inference is not valid for all sets of data

426

(1)

Beware of searching for significance

427

(1)

Section 6.3 Summary

427

(1)

Section 6.3 Exercises

428

(2)

Power and Inference as a Decision

430

(19)

Power

430

(3)

Increasing the power

433

(2)

Inference as decision

435

(1)

Two types of error

435

(1)

Error probabilities

436

(2)

The common practice of testing hypotheses

438

(1)

Section 6.4 Summary

439

(1)

Section 6.4 Exercises

439

(2)

Chapter 6 Exercises

441

(5)

EESEE Case Studies

446

(3)

Inference for Distributions

449

(86)

Introduction

450

(1)

Inference for the Mean of a Population

450

(35)

The t distributions

450

(2)

The one-sample t confidence interval

452

(2)

The one-sample t test

454

(5)

Matched pairs t procedures

459

(3)

Robustness of the t procedures

462

(2)

The power of the t test

464

(1)

Inference for nonnormal populations

465

(5)

Section 7.1 Summary

470

(1)

Section 7.1 Exercises

471

(14)

Comparing Two Means

485

(30)

The two-sample z statistic

486

(2)

The two-sample t procedures

488

(1)

The two-sample t significance test

489

(3)

The two-sample t confidence interval

492

(1)

Robustness of the two-sample procedures

493

(2)

Inference for small samples

495

(3)

Software approximation for the degrees of freedom

498

(1)

The pooled two-sample t procedures

499

(4)

Section 7.2 Summary

503

(1)

Section 7.2 Exercises

504

(11)

Optional Topics in Comparing Distributions

515

(20)

Inference for population spread

516

(1)

The F test for equality of spread

516

(2)

Robustness of normal inference procedures

518

(1)

The power of the two-sample t test

519

(2)

Section 7.3 Summary

521

(1)

Section 7.3 Exercises

521

(3)

Chapter 7 Exercises

524

(9)

EESEE Case Studies

533

(2)

Inference for Proportions

535

(44)

Introduction

536

(1)

Inference for a Single Proportion

536

(19)

Large-sample confidence interval for a single proportion

536

(3)

Plus four confidence interval for a single proportion

539

(1)

Significance test for a single proportion

540

(3)

Confidence intervals provide additional information

543

(2)

Choosing a sample size

545

(3)

Section 8.1 Summary

548

(1)

Section 8.1 Exercises

549

(6)

Comparing Two Proportions

555

(24)

Large-sample confidence interval for a difference in proportions

556

(2)

Plus four confidence interval for a difference in proportions

558

(3)

Significance test for a difference in proportions

561

(2)

Beyond the basics: relative risk

563

(2)

Section 8.2 Summary

565

(1)

Section 8.2 Exercises

566

(4)

Chapter 8 Exercises

570

(8)

EESEE Case Studies

578

(1)

PART 3 Topics in Inference

579

Analysis of Two-Way Tables

581

(52)

Introduction

582

(1)

Data Analysis for Two-Way Tables

582

(9)

The two-way table

582

(2)

Marginal distributions

584

(1)

Describing relations in two-way tables

585

(1)

Conditional distributions

586

(2)

Simpson's paradox

588

(2)

The perils of aggregation

590

(1)

Section 9.1 Summary

590

(1)

Inference for Two-Way Tables

591

(9)

The hypothesis: no association

594

(1)

Expected cell counts

594

(1)

The chi-square test

595

(3)

The chi-square test and the z test

598

(1)

Beyond the basics: meta-analysis

598

(2)

Section 9.2 Summary

600

(1)

Formulas and Models for Two-Way Tables

600

(9)

Computations

600

(1)

Computing conditional distributions

601

(3)

Computing expected cell counts

604

(1)

The X2 statistic and its P-value

605

(1)

Models for two-way tables

606

(2)

Concluding remarks

608

(1)

Section 9.3 Summary

608

(1)

Goodness of Fit

609

(24)

Chapter 9 Exercises

612

(19)

EESEE Case Studies

631

(2)

Inference for Regression

633

(50)

Introduction

634

(1)

Simple Linear Regression

634

(18)

Statistical model for linear regression

634

(1)

Data for simple linear regression

635

(4)

Estimating the regression parameters

639

(5)

Confidence intervals and significance tests

644

(2)

Confidence intervals for mean response

646

(2)

Prediction intervals

648

(2)

Beyond the basics: nonlinear regression

650

(1)

Section 10.1 Summary

651

(1)

More Detail about Simple Linear Regression

652

(31)

Analysis of variance for regression

653

(2)

The ANOVA F test

655

(1)

Calculations for regression inference

656

(8)

Inference for correlation

664

(2)

Section 10.2 Summary

666

(1)

Chapter 10 Exercises

667

(14)

EESEE Case Studies

681

(2)

Multiple Regression

683

(36)

Introduction

684

(1)

Inference for Multiple Regression

684

(6)

Population multiple regression equation

684

(1)

Data for multiple regression

685

(1)

Multiple linear regression model

685

(1)

Estimation of the multiple regression parameters

686

(1)

Confidence intervals and significance tests for regression coefficients

687

(1)

ANOVA table for multiple regression

688

(2)

Squared multiple correlation R2

690

(1)

A Case Study

690

(29)

Preliminary analysis

690

(1)

Relationships between pairs of variables

691

(2)

Regression on high school grades

693

(2)

Interpretation of results

695

(1)

Residuals

695

(1)

Refining the model

696

(1)

Regression on SAT scores

697

(1)

Regression using all variables

698

(3)

Test for a collection of regression coefficients

701

(1)

Beyond the basics: multiple logistic regression

701

(1)

Chapter 11 Summary

702

(1)

Chapter 11 Exercises

703

(14)

EESEE Case Studies

717

(2)

One-Way Analysis of Variance

719

(52)

Introduction

720

(1)

Inference for One-Way Analysis of Variance

720

(17)

Data for one-way ANOVA

720

(1)

Comparing means

721

(2)

The two-sample t statistic

723

(1)

An overview of ANOVA

724

(2)

The ANOVA model

726

(2)

Estimates of population parameters

728

(2)

Testing hypotheses in one-way ANOVA

730

(2)

The ANOVA table

732

(2)

The F test

734

(3)

Comparing the Means

737

(34)

Contrasts

737

(5)

Multiple comparisons

742

(4)

Software

746

(2)

Power

748

(3)

Chapter 12 Summary

751

(1)

Chapter 12 Exercises

751

(18)

EESEE Case Studies

769

(2)

Two-Way Analysis of Variance

771

Introduction

772

(1)

The Two-Way ANOVA Model

772

(11)

Advantages of two-way ANOVA

772

(4)

The two-way ANOVA model

776

(1)

Main effects and interactions

777

(6)

Inference for Two-Way ANOVA

783

The ANOVA table for two-way ANOVA

783

(4)

Chapter 13 Summary

787

(1)

Chapter 13 Exercises

788

Data Appendix

(1)

Tables

(1)

Solutions to Selected Exercises

(1)

Notes and Data Sources

(1)

Index

(1)

Bootstrap Methods and Permutation Tests

(1)

Introduction

(1)

Software

(1)

The Bootstrap Idea

(10)

The big idea: resampling and the bootstrap distribution

(3)

Thinking about the bootstrap idea

(2)

Using software

(1)

Section 14.1 Summary

(1)

Section 14.1 Exercises

(1)

First Steps in Using the Bootstrap

(14)

Bootstrap t confidence intervals

(4)

Bootstrapping to compare two groups

(2)

Beyond the basics: the bootstrap for a scatterplot smoother

(3)

Section 14.2 Summary

(1)

Section 14.2 Exercises

(4)

How Accurate Is a Bootstrap Distribution?

(7)

Bootstrapping small samples

(2)

Bootstrapping a sample median

(2)

Section 14.3 Summary

(1)

Section 14.3 Exercises

(1)

Bootstrap Confidence Intervals

(12)

Bootstrap percentile confidence intervals

(1)

Confidence intervals for the correlation

(3)

More accurate bootstrap confidence intervals: BCa and tilting

(4)

Section 14.4 Summary

(1)

Section 14.4 Exercises

(4)

Significance Testing Using Permutation Tests

Using software

(1)

Permutation tests in practice

(4)

Permutation tests in other settings

(3)

Section 14.5 Summary

(1)

Section 14.5 Exercises

(6)

Chapter 14 Exercises

(6)

Chapter 14 Notes

Nonparametric Tests

(1)

Introduction

(1)

The Wilcoxon Rank Sum Test

(16)

The rank transformation

(1)

The Wilcoxon rank sum test

(2)

The normal approximation

(1)

What hypotheses does Wilcoxon test?

(2)

Ties

(3)

Rank, t, and permutation tests

(1)

Section 15.1 Summary

(1)

Section 15.1 Exercises

(5)

The Wilcoxon Signed Rank Test

(9)

The normal approximation

(1)

Ties

(2)

Section 15.2 Summary

(1)

Section 15.2 Exercises

(4)

The Kruskal-Wallis Test

Hypotheses and assumptions

(1)

The Kruskal-Wallis test

(2)

Section 15.3 Summary

(1)

Section 15.3 Exercises

(3)

Chapter 15 Exercises

(3)

Chapter 15 Notes

Logistic Regression

(1)

Introduction

(1)

The Logistic Regression Model

(5)

Binomial distributions and odds

(2)

Model for logistic regression

(2)

Fitting and interpreting the logistic regression model

(1)

Inference for Logistic Regression

Confidence intervals and significance tests

(7)

Multiple logistic regression

(1)

Chapter 16 Summary

(1)

Chapter 16 Exercises

(9)

Chapter 16 Notes

Statistics for Quality: Control and Capability

(62)

Introduction

(1)

Processes and Statistical Process Control

(20)

Describing processes

(3)

Statistical process control

(1)

x charts for process monitoring

(4)

s charts for process monitoring

(6)

Section 17.1 Summary

(1)

Section 17.1 Exercises

(6)

Using Control Charts

(18)

x and R charts

(1)

Additional out-of-control signals

(2)

Setting up control charts

(4)

Comments on statistical control

(4)

Don't confuse control with capability!

(1)

Section 17.2 Summary

(1)

Section 17.2 Exercises

(5)

Process Capability Indexes

(12)

The capability indexes Cp and Cpk

(2)

Cautions about capability indexes

(2)

Section 17.3 Summary

(1)

Section 17.3 Exercises

(5)

Control Charts for Sample Proportions

(10)

Control limits for p charts

(4)

Section 17.4 Summary

(1)

Section 17.4 Exercises

(2)

Chapter 17 Exercises

(3)

Chapter 17 Notes

Amazon no longer offers textbook rentals. We do!

Introduction to the Practice of Statistics w/CD-ROM

Introduction to the Practice of Statistics w/CD-ROM

9780716764007

0716764008

Summary

Table of Contents

Supplemental Materials

Write a Review

Amazon no longer offers textbook rentals. We do!

Introduction to the Practice of Statistics w/CD-ROM

Introduction to the Practice of Statistics w/CD-ROM

9780716764007

0716764008

Summary

Table of Contents

Supplemental Materials

Write a Review

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