Wednesday, February 13, 2019

Statistics: The Art and Science of Learning from Data, 4th Edition

Statistics: The Art and Science of Learning from Data, 4th Edition

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Statistics: The Art and Science of Learning from Data, 4th Edition Bank Test , Statistics: The Art and Science of Learning from Data, 4th Edition Textbook , Statistics: The Art and Science of Learning from Data, 4th Edition PDF , Statistics: The Art and Science of Learning from Data, 4th Edition eBook , Alan Agresti, University of Florida Christine A. Franklin, University of Georgia Bernhard Klingenberg, Williams College

Category : Higher Education

Table of Contents

Preface

 

PART ONE: 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 Review 1 (ONLINE)

 

PART TWO: 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

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

            Chapter Summary

            Chapter Problems

 

            Part Review 2 (ONLINE)

 

PART THREE: 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

            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 Review 3 (ONLINE)

 

PART FOUR: ANALYZING ASSOCIATION AND EXTENDED STATISTICAL METHODS

 

11. Analyzing the Association Between Categorical Variables

11.1 Independence and Dependence (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 Fisher’s Exact and Permutation Tests

            Chapter Summary

            Chapter Problems

 

12. Analyzing the Association Between Quantitative Variables: Regression Analysis

12.1 Modeling How Two Variables Are Related

12.2 Inference About Model Parameters and the Association

12.3 Describing the Strength of Association

12.4 How 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 R2 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 Review 4 (ONLINE)

 

Tables

Answers

Index

Index of Applications

Photo Credits

Instalant Download Statistics: The Art and Science of Learning from Data, 4th Edition by Alan Agresti, University of Florida Christine A. Franklin, University of Georgia Bernhard Klingenberg, Williams College ZIP OR PDF

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