Statistics: Pearson New International Edition

The Art and Science of Learning from Data
3e édition

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Pearson Education
Alan Agresti, Christine Franklin,
BISAC Subject Heading
MAT029000 MATHEMATICS / Probability & Statistics
BIC subject category (UK)
PBT Probability & statistics
Code publique Onix
05 Enseignement supérieur
Date de première publication du titre
01 novembre 2013
Subject Scheme Identifier Code
Classification thématique Thema: Probabilité et statistiques

VitalSource eBook

Date de publication
01 novembre 2013
Nombre de pages de contenu principal : 816
Code interne
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Part 1: Gathering and Exploring Data


1. Statistics: The Art and Science of Learning from Data

1.1 Using Data to Answer Statistical Questions

1.2 Sample Versus Population

1.3 Using Calculators and Computers

Chapter Summary

Chapter Problems


2. Exploring Data with Graphs and Numerical Summaries

2.1 Different Types of Data

2.2 Graphical Summaries of Data

2.3 Measuring the Center of Quantitative Data

2.4 Measuring the Variability of Quantitative Data

2.5 Using Measures of Position to Describe Variability

2.6 Recognizing and Avoiding Misuses of Graphical Summaries

Chapter Summary

Chapter Problems


3. Association: Contingency, Correlation, and Regression

3.1 The Association Between Two Categorical Variables

3.2 The Association Between Two Quantitative Variables

3.3 Predicting the Outcome of a Variable

3.4 Cautions in Analyzing Associations

Chapter Summary

Chapter Problems


4. Gathering Data

4.1 Experimental and Observational Studies

4.2 Good and Poor Ways to Sample

4.3 Good and Poor Ways to Experiment

4.4 Other Ways to Conduct Experimental and Nonexperimental Studies

Chapter Summary

Chapter Problems


Part 1 Review

Part 1 Questions

Part 1 Exercises


Part 2: Probability, Probability Distributions, and Sampling Distributions


5. Probability in Our Daily Lives

5.1 How Probability Quantifies Randomness

5.2 Finding Probabilities

5.3 Conditional Probability: The Probability of A Given B

5.4 Applying the Probability Rules

Chapter Summary

Chapter Problems


6. Probability Distributions

6.1 Summarizing Possible Outcomes and Their Probabilities

6.2 Probabilities for Bell-Shaped Distributions

6.3 Probabilities When Each Observation Has Two Possible Outcomes

Chapter Summary

Chapter Problems


7. Sampling Distributions

7.1 How Sample Proportions Vary Around the Population Proportion

7.2 How Sample Means Vary Around the Population Mean

7.3 The Binomial Distribution Is a Sampling Distribution (Optional)

Chapter Summary

Chapter Problems


Part 2 Review

Part 2 Questions

Part 2 Exercises


Part 3: Inferential Statistics


8. Statistical Inference: Confidence Intervals

8.1 Point and Interval Estimates of Population Parameters

8.2 Constructing a Confidence Interval to Estimate a Population Proportion

8.3 Constructing a Confidence Interval to Estimate a Population Mean

8.4 Choosing the Sample Size for a Study

8.5 Using Computers to Make New Estimation Methods Possible

Chapter Summary

Chapter Problems


9. Statistical Inference: Significance Tests about Hypotheses

9.1 Steps for Performing a Significance Test

9.2 Significance Tests about Proportions

9.3 Significance Tests about Means

9.4 Decisions and Types of Errors in Significance Tests

9.5 Limitations of Significance Tests

9.6 The Likelihood of a Type II Error (Not Rejecting H0, Even Though It’s False)

Chapter Summary
Chapter Problems


10. Comparing Two Groups

10.1 Categorical Response: Comparing Two Proportions

10.2 Quantitative Response: Comparing Two Means

10.3 Other Ways of Comparing Means and Comparing Proportions

10.4 Analyzing Dependent Samples

10.5 Adjusting for the Effects of Other Variables

Chapter Summary
Chapter Problems


Part 3 Review

Part 3 Questions

Part 3 Exercises


Part 4: Analyzing Association and Extended Statistical Methods


11. Analyzing the Association Between Categorical Variables

11.1 Independence and Association

11.2 Testing Categorical Variables for Independence

11.3 Determining the Strength of the Association

11.4 Using Residuals to Reveal the Pattern of Association

11.5 Small Sample Sizes: Fisher’s Exact Test

Chapter Summary
Chapter Problems


12. Analyzing the Association Between Quantitative Variables: Regression Analysis

12.1 Model How Two Variables Are Related

12.2 Describe Strength of Association

12.3 Make Inference About the Association

12.4How the Data Vary Around the Regression Line

12.5 Exponential Regression: A Model for Nonlinearity

Chapter Summary
Chapter Problems


13. Multiple Regression

13.1 Using Several Variables to Predict a Response

13.2 Extending the Correlation and R-squared for Multiple Regression

13.3 Using Multiple Regression to Make Inferences

13.4 Checking a Regression Model Using Residual Plots

13.5 Regression and Categorical Predictors

13.6 Modeling a Categorical Response

Chapter Summary
Chapter Problems


14. Comparing Groups: Analysis of Variance Methods

14.1 One-Way ANOVA: Comparing Several Means

14.2 Estimating Differences in Groups for a Single Factor  

14.3 Two-Way ANOVA

Chapter Summary
Chapter Problems


15. Nonparametric Statistics

15.1 Compare Two Groups by Ranking

15.2 Nonparametric Methods For Several Groups and for Matched Pairs

Chapter Summary
Chapter Problems


PART 4 Review

Part 4 Questions

Part 4 Exercises





Index of Applications

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