Statistics: The Art and Science of Learning from Data

Cover
Title Page
Copyright
Dedication
Contents
An Introduction to the Web Apps
Preface
About the Authors
Part One: Gathering and Exploring Data
	Chapter 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
	Chapter 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
	Chapter 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 in Analyzing Associations
		Chapter Summary
		Chapter Exercises
	Chapter 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
Part Two: Probability, Probability Distributions, and Sampling Distributions
	Chapter 5. Probability in Our DailyLives
		5.1 How Probability Quantifies Randomness
		5.2 Finding Probabilities
		5.3 Conditional Probability
		5.4 Applying the Probability Rules
		Chapter Summary
		Chapter Exercises
	Chapter 6. Random Variables and Probability Distributions
		6.1 Summarizing Possible Outcomes and Their Probabilities
		6.2 Probabilities for Bell-Shaped Distributions: The Normal Distribution
		6.3 Probabilities When Each Observation Has Two Possible Outcomes: The Binomial Distribution
		Chapter Summary
		Chapter Exercises
	Chapter 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 Using the Bootstrap to Find Sampling Distributions
		Chapter Summary
		Chapter Exercises
Part Three: Inferential Statistics
	Chapter 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
	Chapter 9. Statistical Inference: Significance Tests About Hypotheses
		9.1 Steps for Performing a Significance Test
		9.2 Significance Test About a Proportion
		9.3 Significance Test 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 II Error and the Power of a Test
		Chapter Summary
		Chapter Exercises
	Chapter 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
Part Four: Extended Statistical Methods and Models for Analyzing Categorical and Quantitative Variables
	Chapter 11. Categorical Data Analysis
		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 Exercises
	Chapter 12. Regression Analysis
		12.1 The Linear Regression Model
		12.2 Inference About Model Parameters and the Relationship
		12.3 Describing the Strength of the Relationship
		12.4 How the Data Vary Around the Regression Line
		12.5 Exponential Regression: A Model for Nonlinearity
		Chapter Summary
		Chapter Exercises
	Chapter 13. Multiple Regression
		13.1 Using Several Variables to Predict a Response
		13.2 Extending the Correlation Coefficient and R2 for Multiple Regression
		13.3 Inferences Using Multiple Regression
		13.4 Checking a Regression Model Using Residual Plots
		13.5 Regression and Categorical Predictors
		13.6 Modeling a Categorical Response: Logistic Regression
		Chapter Summary
		Chapter Exercises
	Chapter 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: Exploring Two Factors and Their Interaction
		Chapter Summary
		Chapter Exercises
	Chapter 15. Nonparametric Statistics
		15.1 Compare Two Groups by Ranking
		15.2 Nonparametric Methods for Several Groups and for Dependent Samples
		Chapter Summary
		Chapter Exercises
Appendix
Answers
Index
	A
	B
	C
	D
	E
	F
	G
	H
	I
	J
	K
	L
	M
	N
	O
	P
	Q
	R
	S
	T
	U
	V
	W
	X
	Y
	Z
Index of Applications
	A
	B
	C
	D
	E
	F
	G
	H
	I
	J
	K
	L
	M
	N
	O
	P
	Q
	R
	S
	T
	U
	V
	W
Credits