Description
Statistics The Art and Science of Learning from Data 5th Edition Agresti – Solution Manual
Solution Manual for Statistics The Art and Science of Learning from Data, 5th Edition, Alan Agresti, Christine A. Franklin, Bernhard Klingenberg, ISBN-13: 9780136468769
Table of Contents
I: 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 Organizing Data, Statistical Software, and the New Field of Data Science
Chapter Summary
Chapter Exercises
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 Linear Transformations and Standardizing
2.7 Recognizing and Avoiding Misuses of Graphical Summaries
Chapter Summary
Chapter Exercises
3. Exploring Relationships Between Two Variables
3.1 The Association Between Two Categorical Variables
3.2 The Relationship Between Two Quantitative Variables
3.3 Linear Regression: Predicting the Outcome of a Variable
3.4 Cautions inAnalyzing Associations
Chapter Summary
Chapter Exercises
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 Exercises
II: 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 Exercises
6. Random Variables and 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 Exercises
7. Sampling Distributions
7.1 How Sample Proportions VaryAround the Population Proportion
7.2 How Sample Means VaryAround the Population Mean
7.3 Using the Bootstrap to Find Sampling Distributions
Chapter Summary
Chapter Exercises
III: INFERENTIAL STATISTICS
8. Statistical Inference: Confidence Intervals
8.1 Point and Interval Estimates of Population Parameters
8.2 Confidence Interval for a Population Proportion
8.3 Confidence Interval for a Population Mean
8.4 Bootstrap Confidence Intervals
Chapter Summary
Chapter Exercises
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 a Mean
9.4 Decisions and Types of Errors in Significance Tests
9.5 Limitations of Significance Tests
9.6 The Likelihood of a Type IIError
Chapter Summary
Chapter Exercises
10. Comparing Two Groups
10.1 Categorical Response: Comparing Two Proportions
10.2 Quantitative Response: Comparing Two Means
10.3 Comparing Two Groups with Bootstrap or Permutation Resampling
10.4 Analyzing Dependent Samples
10.5 Adjusting for the Effects of Other Variables
Chapter Summary
Chapter Exercises
IV: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 ofAssociation
11.5 Fisher’s Exact and Permutation Tests
Chapter Summary
Chapter Exercises
12. Analyzing the Association Between Quantitative Variables: RegressionAnalysis
12.1 Modeling How Two Variables Are Related
12.2 Inference About Model Parameters and the Association
12.3 Describing the Strength ofAssociation
12.4 How the Data VaryAround the Regression Line
12.5 Exponential Regression:A Model for Nonlinearity
Chapter Summary
Chapter Exercises
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 Exercises
14. Comparing Groups:Analysis of Variance Methods
14.1 One-WayANOVA: Comparing Several Means
14.2 Estimating Differences in Groups for a Single Factor
14.3 Two-WayANOVA
Chapter Summary
Chapter Exercises
15. Nonparametric Statistics
15.1 Compare Two Groups by Ranking
15.2 Nonparametric Methods for Several Groups and for Matched Pairs
Chapter Summary
