Djvu Statistics the Art and Science of Learning From Data
Statistics The Art and Science of Learning From Information
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
Function I Gathering and Exploring Information
Chapter 1 Statistics: The Art and
Scientific discipline of Learning from
Information 28
1.1 Using Data to Answer Statistical Questions 29
1.2 Sample Versus Population 34
1.3 Using Calculators and Computers 43
Affiliate Summary 49
Chapter Problems 50
Chapter 2 Exploring Data with
Graphs and Numerical
Summaries 52
two.1 Different Types of Information 53
2.2 Graphical Summaries of Data 58
2.three Measuring the Center of Quantitative Data 76
ii.4 Measuring the Variability of Quantitative Data 84
2.v Using Measures of Position to Depict Variability 92
2.6 Recognizing and Avoiding Misuses of Graphical
Summaries 102
Chapter Summary 108
Chapter Problems 109
Chapter three Clan: Contingency,
Correlation, and
Regression 117
iii.1 The Association Between Two Chiselled
Variables 119
iii.2 The Association Between Two Quantitative
Variables 127
3.3 Predicting the Outcome of a Variable 139
3.4 Cautions in Analyzing Associations 154
Affiliate Summary 170
Chapter Problems 171
Chapter iv Gathering Data 179
4.1 Experimental and Observational Studies 180
4.ii Good and Poor Means to Sample 188
4.three Expert and Poor Ways to Experiment 198
4.iv Other Ways to Conduct Experimental and
Nonexperimental Studies 204
Chapter Summary 216
Chapter Problems 216
Part Review ane Online
Office 2 Probability, Probability Distributions,
and Sampling Distributions
Chapter five Probability in Our Daily
Lives 226
5.1 How Probability Quantifies Randomness 227
five.two Finding Probabilities 234
five.3 Conditional Probability 247
5.iv Applying the Probability Rules 258
Chapter Summary 273
Chapter Issues 273
Chapter 6 Probability Distributions 280
6.1 Summarizing Possible Outcomes and Their
Probabilities 281
6.2 Probabilities for Bell-Shaped Distributions 293
half dozen.iii Probabilities When Each Ascertainment Has Two Possible
Outcomes 305
Chapter Summary 315
Chapter Problems 316
Chapter vii Sampling Distributions 324
7.1 How Sample Proportions Vary Around the Population
Proportion 325
seven.2 How Sample Means Vary Around the Population
Mean 337
Chapter Summary 352
Chapter Problems 352
Part Review 2 Online
Office Three Inferential Statistics
Chapter 8 Statistical Inference:
Confidence Intervals 360
8.1 Point and Interval Estimates of Population
Parameters 361
eight.2 Constructing a Confidence Interval to Estimate a
Population Proportion 367
8.iii Constructing a Confidence Interval to Guess a
Population Mean 380
8.4 Choosing the Sample Size for a Study 391
eight.5 Using Computers to Make New Interpretation Methods
Possible 400
Chapter Summary 404
Chapter Problems 404
Chapter ix Statistical Inference:
Significance Tests About
Hypotheses 412
9.1 Steps for Performing a Significance
Test 413
9.2 Significance Tests About Proportions 418
9.3 Significance Tests Almost Means 434
ix.4 Decisions and Types of Errors in Significance
Tests 444
ix.5 Limitations of Significance Tests 449
ix.6 The Likelihood of a Blazon Two Fault and the Ability
of a Test 456
Affiliate Summary 463
Chapter Problems 464
Chapter 10 Comparison 2 Groups 470
ten.1 Categorical Response: Comparing Two
Proportions 472
x.2 Quantitative Response: Comparison Two Means 486
10.3 Other Ways of Comparing Means, Including a
Permutation Test 498
ten.iv Analyzing Dependent Samples 513
ten.5 Adjusting for the Effects of Other Variables 524
Affiliate Summary 530
Chapter Issues 531
Role Review 3 Online
Function Four Analyzing Clan and
Extended Statistical Methods
Chapter xi Analyzing the Clan
Between Categorical
Variables 542
11.ane Independence and Dependence (Association) 543
11.2 Testing Categorical Variables for Independence 548
11.3 Determining the Strength of the Association 563
11.4 Using Residuals to Reveal the Blueprint of
Association 572
11.5 Fishers Exact and Permutation Tests 576
Chapter Summary 585
Chapter Problems 585
Chapter 12 Analyzing the Clan
Between Quantitative Variables:
Regression Analysis 592
12.1 Modeling How Two Variables Are Related 593
12.2 Inference About Model Parameters and the
Association 603
12.3 Describing the Strength of Association 610
12.4 How the Information Vary Around the Regression Line 620
12.5 Exponential Regression: A Model for Nonlinearity 631
Affiliate Summary 637
Chapter Issues 638
Chapter thirteen Multiple Regression 644
13.1 Using Several Variables to Predict a Response 645
13.2 Extending the Correlation and R2 for Multiple
Regression 651
13.3 Inferences Using Multiple Regression 657
13.four Checking a Regression Model Using Balance Plots 668
13.5 Regression and Chiselled Predictors 674
13.6 Modeling a Chiselled Response 680
Chapter Summary 689
Chapter Problems 690
Chapter fourteen Comparing Groups:
Analysis of Variance
Methods 695
14.1 One-Manner ANOVA: Comparing Several Means 696
14.ii Estimating Differences in Groups for a Unmarried
Factor 706
14.3 2-Way ANOVA 716
Affiliate Summary 730
Chapter Problems 730
Affiliate xv Nonparametric Statistics 736
15.1 Compare Two Groups by Ranking 737
15.2 Nonparametric Methods for Several Groups and for
Matched Pairs 748
Affiliate Summary 759
Chapter Bug 759
Function Review 4 Online
Appendix A-ane
Answers A-7
Index I-ane
Alphabetize of Applications I-9
Credits C-i
A Guide to Learning From the Fine art in This Text D-1
Dataset Files D-2
A Guide to Choosing a Statistical Method D-three
Summary of Key Notations and Formulas D-4
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