Statistics the Art and Science of Learning From Data by Agresti Franklin Klingenberg 4th Edition
Statistics The Fine art and Science of Learning From Data
Informasi Barang
Spesifikasi
| Kategori | : | Import |
|---|---|---|
| Berat | : | v gram |
| Asal Barang | : | Lokal |
Deskripsi
Statistics: The Art and Science of Learning From Data
Author: Alan Agresti, Christine A. Franklin, Bernhard Klingenberg
Publisher: Pearson
Year: 2017
Pdf size: 42,ii MB
Pages: 817
Contents
Preface 9
Office I Gathering and Exploring Data
Chapter 1 Statistics: The Art and
Science of Learning from
Information 28
1.one Using Data to Answer Statistical Questions 29
1.2 Sample Versus Population 34
one.3 Using Calculators and Computers 43
Chapter Summary 49
Chapter Problems l
Affiliate 2 Exploring Data with
Graphs and Numerical
Summaries 52
2.one Different Types of Data 53
2.two Graphical Summaries of Data 58
2.3 Measuring the Heart of Quantitative Data 76
2.4 Measuring the Variability of Quantitative Data 84
2.5 Using Measures of Position to Describe Variability 92
2.6 Recognizing and Avoiding Misuses of Graphical
Summaries 102
Chapter Summary 108
Chapter Issues 109
Chapter 3 Association: Contingency,
Correlation, and
Regression 117
3.1 The Association Betwixt Two Categorical
Variables 119
3.ii The Clan Between Two Quantitative
Variables 127
three.3 Predicting the Outcome of a Variable 139
3.iv Cautions in Analyzing Associations 154
Chapter Summary 170
Chapter Problems 171
Chapter 4 Gathering Data 179
4.1 Experimental and Observational Studies 180
4.ii Skillful and Poor Ways to Sample 188
4.3 Expert and Poor Ways to Experiment 198
4.iv Other Ways to Deport Experimental and
Nonexperimental Studies 204
Chapter Summary 216
Chapter Problems 216
Part Review 1 Online
Part Two Probability, Probability Distributions,
and Sampling Distributions
Chapter five Probability in Our Daily
Lives 226
5.1 How Probability Quantifies Randomness 227
five.ii Finding Probabilities 234
5.3 Conditional Probability 247
5.iv Applying the Probability Rules 258
Chapter Summary 273
Affiliate Problems 273
Affiliate half dozen Probability Distributions 280
6.1 Summarizing Possible Outcomes and Their
Probabilities 281
six.2 Probabilities for Bell-Shaped Distributions 293
vi.3 Probabilities When Each Observation Has Ii Possible
Outcomes 305
Chapter Summary 315
Chapter Problems 316
Affiliate 7 Sampling Distributions 324
seven.1 How Sample Proportions Vary Around the Population
Proportion 325
7.2 How Sample Ways Vary Around the Population
Mean 337
Chapter Summary 352
Chapter Problems 352
Part Review 2 Online
Part Three Inferential Statistics
Chapter eight Statistical Inference:
Confidence Intervals 360
eight.1 Signal and Interval Estimates of Population
Parameters 361
8.two Amalgam a Conviction Interval to Guess a
Population Proportion 367
8.three Constructing a Conviction Interval to Guess a
Population Hateful 380
8.iv Choosing the Sample Size for a Study 391
eight.5 Using Computers to Make New Estimation Methods
Possible 400
Affiliate Summary 404
Affiliate Bug 404
Chapter nine Statistical Inference:
Significance Tests About
Hypotheses 412
9.1 Steps for Performing a Significance
Test 413
ix.ii Significance Tests About Proportions 418
9.iii Significance Tests Virtually Means 434
nine.4 Decisions and Types of Errors in Significance
Tests 444
9.five Limitations of Significance Tests 449
ix.6 The Likelihood of a Type II Fault and the Power
of a Test 456
Chapter Summary 463
Affiliate Bug 464
Chapter ten Comparing Two Groups 470
10.1 Categorical Response: Comparison Two
Proportions 472
10.2 Quantitative Response: Comparing Two Means 486
x.iii Other Ways of Comparison Ways, Including a
Permutation Test 498
ten.4 Analyzing Dependent Samples 513
10.v Adjusting for the Furnishings of Other Variables 524
Affiliate Summary 530
Chapter Problems 531
Role Review 3 Online
Part Four Analyzing Clan and
Extended Statistical Methods
Affiliate eleven Analyzing the Association
Between Categorical
Variables 542
11.1 Independence and Dependence (Association) 543
xi.ii Testing Categorical Variables for Independence 548
11.3 Determining the Strength of the Association 563
11.4 Using Residuals to Reveal the Pattern of
Association 572
11.5 Fishers Exact and Permutation Tests 576
Chapter Summary 585
Chapter Issues 585
Chapter 12 Analyzing the Association
Betwixt Quantitative Variables:
Regression Analysis 592
12.one Modeling How Ii Variables Are Related 593
12.2 Inference About Model Parameters and the
Association 603
12.3 Describing the Strength of Clan 610
12.4 How the Data Vary Effectually the Regression Line 620
12.5 Exponential Regression: A Model for Nonlinearity 631
Chapter Summary 637
Chapter Problems 638
Chapter 13 Multiple Regression 644
xiii.1 Using Several Variables to Predict a Response 645
thirteen.two Extending the Correlation and R2 for Multiple
Regression 651
thirteen.3 Inferences Using Multiple Regression 657
thirteen.4 Checking a Regression Model Using Residual Plots 668
13.5 Regression and Chiselled Predictors 674
13.half-dozen Modeling a Categorical Response 680
Chapter Summary 689
Affiliate Problems 690
Chapter 14 Comparing Groups:
Assay of Variance
Methods 695
14.1 I-Mode ANOVA: Comparing Several Means 696
14.ii Estimating Differences in Groups for a Single
Cistron 706
14.iii Two-Way ANOVA 716
Chapter Summary 730
Affiliate Problems 730
Chapter 15 Nonparametric Statistics 736
fifteen.i Compare Two Groups past Ranking 737
15.2 Nonparametric Methods for Several Groups and for
Matched Pairs 748
Chapter Summary 759
Chapter Issues 759
Part Review iv Online
Appendix A-1
Answers A-seven
Index I-ane
Alphabetize of Applications I-ix
Credits C-1
A Guide to Learning From the Art in This Text D-1
Dataset Files D-2
A Guide to Choosing a Statistical Method D-3
Summary of Key Notations and Formulas D-4
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