Stats: Data and Models (4th Global Edition)

$19.99

Download Stats: Data and Models (4th Global Edition) written by Richard D. De Veaux, Paul D. Velleman, David E. Bock in PDF format. This book is under the category Statistics and bearing the isbn/isbn13 number 1292101636/9781292101637. You may reffer the table below for additional details of the book.

SKU: 743c41a92151 Category: Tag:

Specifications

book-author

Richard D. De Veaux, Paul D. Velleman, David E. Bock

publisher

Pearson

file-type

PDF

pages

996 pages

language

English

asin

B01ITS8OZ2

isbn10

1292101636

isbn13

9781292101637


Book Description

Richard De Veaux; Paul Velleman; and David Bock wrote Stats: Data and Models 4e (Global) with the goal that college students and instructors have as much fun reading it as they did writing it. Maintaining a conversational; humorous; and informal writing style; this new edition engages students from the first page. The authors focus on statistical thinking throughout the text and rely on technology for calculations. As a result; university students can focus on developing their conceptual understanding. Innovative Think/Tell/Show examples to give stats students a problem-solving framework and; more importantly; a way to think through any statistics problem and present their results. The Fourth Edition is updated with instructor podcasts; video lectures; and new examples to keep material fresh; current; and relevant to today’s students.

P.S A newer edition is also available. See related ebooks below

NOTE: This sale only includes the ebook Stats: Data and Models 4th Edition (global) in PDF. No access codes included.

Additional information

book-author

Richard D. De Veaux, Paul D. Velleman, David E. Bock

publisher

Pearson

file-type

PDF

pages

996 pages

language

English

asin

B01ITS8OZ2

isbn10

1292101636

isbn13

9781292101637

Table of contents


Table of contents :
Cover……Page 1
Title Page……Page 2
Copyright Page……Page 3
Table of Contents……Page 6
Preface……Page 10
Supplements……Page 14
Acknowledgments……Page 17
1.1 What Is Statistics?……Page 18
1.2 Data……Page 20
1.3 Variables……Page 22
Chapter 2 Displaying and Describing Categorical Data……Page 33
2.1 Summarizing and Displaying a Single Categorical Variable……Page 34
2.2 Exploring the Relationship Between Two Categorical Variables……Page 37
3.1 Displaying Quantitative Variables……Page 62
3.2 Shape……Page 67
3.3 Center……Page 70
3.4 Spread……Page 71
3.5 Boxplots and 5-Number Summaries……Page 73
3.6 The Center of Symmetric Distributions: The Mean……Page 76
3.7 The Spread of Symmetric Distributions: The Standard Deviation……Page 78
3.8 Summary—What to Tell About a Quantitative Variable……Page 80
Chapter 4 Understanding and Comparing Distributions……Page 101
4.1 Comparing Groups with Histograms……Page 102
4.2 Comparing Groups with Boxplots……Page 103
4.3 Outliers……Page 106
4.4 Timeplots: Order, Please!……Page 108
4.5 Re-Expressing Data: A First Look……Page 111
Chapter 5 The Standard Deviation as a Ruler and the Normal Model……Page 129
5.1 Standardizing with z-Scores……Page 130
5.2 Shifting and Scaling……Page 132
5.3 Normal Models……Page 136
5.4 Finding Normal Percentiles……Page 140
5.5 Normal Probability Plots……Page 146
Chapter 6 Scatterplots, Association, and Correlation……Page 168
6.1 Scatterplots……Page 169
6.2 Correlation……Page 172
6.3 Warning: Correlation fi Causation……Page 180
*6.4 Straightening Scatterplots……Page 182
Chapter 7 Linear Regression……Page 199
7.1 Least Squares: The Line of “Best Fit”……Page 200
7.2 The Linear Model……Page 201
7.3 Finding the Least Squares Line……Page 202
7.4 Regression to the Mean……Page 206
7.5 Examining the Residuals……Page 209
7.6 R2—The Variation Accounted For by the Model……Page 211
7.7 Regression Assumptions and Conditions……Page 213
8.1 Examining Residuals……Page 236
8.2 Extrapolation: Reaching Beyond the Data……Page 239
8.3 Outliers, Leverage, and Influence……Page 243
8.4 Lurking Variables and Causation……Page 246
8.5 Working with Summary Values……Page 247
Chapter 9 Re-expressing Data: Get It Straight!……Page 264
9.1 Straightening Scatterplots – The Four Goals……Page 265
9.2 Finding a Good Re-Expressio……Page 269
Chapter 10 Understanding Randomness……Page 297
10.1 What Is Randomness?……Page 298
10.2 Simulating by Hand……Page 299
Chapter 11 Sample Surveys……Page 311
11.1 The Three Big Ideas of Sampling……Page 312
11.2 Populations and Parameters……Page 315
11.3 Simple Random Samples……Page 316
11.4 Other Sampling Designs……Page 317
11.5 From the Population to the Sample: You Can’t Always Get What You Want……Page 322
11.6 The Valid Survey……Page 323
11.7 Common Sampling Mistakes, or How to Sample Badly……Page 324
12.1 Observational Studies……Page 335
12.2 Randomized, Comparative Experiments……Page 336
12.3 The Four Principles of Experimental Design……Page 338
12.4 Control Treatments……Page 343
12.5 Blocking……Page 346
12.6 Confounding……Page 347
13.1 Random Phenomena……Page 365
13.2 Modeling Probability……Page 368
13.3 Formal Probability……Page 370
14.1 The General Addition Rule……Page 383
14.2 Conditional Probability and the General Multiplication Rule……Page 388
14.3 Independence……Page 390
14.4 Picturing Probability: Tables, Venn Diagrams, and Trees……Page 392
14.5 Reversing the Conditioning and Bayes’ Rule……Page 395
15.1 Center: The Expected Value……Page 406
15.2 Spread: The Standard Deviation……Page 408
15.3 Shifting and Combining Random Variables……Page 411
15.4 Continuous Random Variables……Page 417
16.1 Bernoulli Trials……Page 429
16.2 The Geometric Model……Page 430
16.3 The Binomial Model……Page 433
16.4 Approximating the Binomial with a Normal Model……Page 436
16.5 The Continuity Correction……Page 438
16.6 The Poisson Model……Page 440
16.7 Other Continuous Random Variables: The Uniform and the Exponential……Page 442
17.1 Sampling Distribution of a Proportion……Page 460
17.2 When Does the Normal Model Work? Assumptions and Conditions……Page 464
17.3 The Sampling Distribution of Other Statistics……Page 468
17.4 The Central Limit Theorem: The Fundamental Theorem of Statistics……Page 469
17.5 Sampling Distributions: A Summary……Page 475
Chapter 18 Confidence Intervals for Proportions……Page 489
18.1 A Confidence Interval……Page 490
18.2 Interpreting Confidence Intervals: What Does 95% Confidence Really Mean?……Page 492
18.3 Margin of Error: Certainty vs. Precision……Page 494
18.4 Assumptions and Conditions……Page 496
Chapter 19 Testing Hypotheses About Proportions……Page 511
19.1 Hypotheses……Page 512
19.2 P-Values……Page 513
19.3 The Reasoning of Hypothesis Testing……Page 515
19.4 Alternative Alternatives……Page 518
19.5 P-Values and Decisions: What to Tell About a Hypothesis Test……Page 521
Chapter 20 Inferences About Means……Page 535
20.1 Getting Started: The Central Limit Theorem (Again)……Page 536
20.2 Gosset’s t……Page 537
20.4 A Hypothesis Test for the Mean……Page 546
20.5 Choosing the Sample Size……Page 551
21.1 Choosing Hypotheses……Page 565
21.2 How to Think About P-Values……Page 567
21.3 Alpha Levels……Page 571
21.4 Critical Values for Hypothesis Tests……Page 574
21.5 Errors……Page 577
Chapter 22 Comparing Groups……Page 602
22.1 The Standard Deviation of a Difference……Page 603
22.2 Assumptions and Conditions for Comparing Proportions……Page 605
22.3 A Confidence Interval for the Difference Between Two Proportions……Page 606
22.4 The Two Sample z-Test: Testing for the Difference Between Proportions……Page 609
22.5 A Confidence Interval for the Difference Between Two Means……Page 613
22.6 The Two-Sample t-Test: Testing for the Difference Between Two Means……Page 617
22.7 The Pooled t-Test: Everyone into the Pool?……Page 623
Chapter 23 Paired Samples and Blocks……Page 647
23.1 Paired Data……Page 648
23.2 Assumptions and Conditions……Page 649
23.3 Confidence Intervals for Matched Pairs……Page 654
23.4 Blocking……Page 657
24.1 Goodness-of-Fit Tests……Page 672
24.2 Chi-Square Test of Homogeneity……Page 680
24.3 Examining the Residuals……Page 684
24.4 Chi-Square Test of Independence……Page 686
Chapter 25 Inferences for Regression……Page 706
25.1 The Population and the Sample……Page 707
25.2 Assumptions and Conditions……Page 708
25.3 Intuition About Regression Inference……Page 713
25.4 Regression Inference……Page 716
25.5 Standard Errors for Predicted Values……Page 722
25.6 Confidence Intervals for Predicted Values……Page 723
25.7 Logistic Regression……Page 725
Chapter *26 Analysis of Variance……Page 764
26.1 Testing Whether the Means of Several Groups Are Equal……Page 766
26.2 The ANOVA Table……Page 770
26.3 Assumptions and Conditions……Page 776
26.4 Comparing Means……Page 782
26.5 ANOVA on Observational Data……Page 784
Chapter 27 Multifactor Analysis of Variance……Page 799
27.1 A Two Factor ANOVA Model……Page 800
27.2 Assumptions and Conditions……Page 801
27.3 Interactions……Page 813
28.1 What Is Multiple Regression?……Page 834
28.2 Interpreting Multiple Regression Coefficients……Page 836
28.3 The Multiple Regression Model—Assumptions and Conditions……Page 838
28.4 Multiple Regression Inference……Page 842
28.5 Comparing Multiple Regression Models……Page 849
Chapter 29 Multiple Regression Wisdom (available online)……Page 876
29.1 Indicators……Page 878
29.2 Diagnosing Regression Models: Looking at the Cases……Page 882
29.3 Building Multiple Regression Models……Page 889
A Answers……Page 912
B Photo Acknowledgments……Page 962
C……Page 964
E……Page 966
J……Page 967
N……Page 968
P……Page 969
R……Page 970
S……Page 971
V……Page 972
Z……Page 973
D Tables and Selected Formulas……Page 980

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