Introduction to probability and statistics

Cover
Brief Contents
Contents
Preface
Introduction: What Is Statistics?
	The Population and the Sample
	Descriptive and Inferential Statistics
	Achieving the Objective of Inferential Statistics: The Necessary Steps
	Keys for Successful Learning
Chapter 1: Describing Data with Graphs
	1.1 Variables and Data
	1.2 Graphs for Categorical Data
	1.3 Graphs for Quantitative Data
	1.4 Relative Frequency Histograms
	Chapter Review
	Technology Today
	Reviewing What You've Learned
	Case Study: How Is Your Blood Pressure?
Chapter 2: Describing Data with Numerical Measures
	Introduction
	2.1 Measures of Center
	2.2 Measures of Variability
	2.3 Understanding and Interpreting the Standard Deviation
	2.4 Measures of Relative Standing
	Chapter Review
	Technology Today
	Reviewing What You've Learned
	Case Study: The Boys of Summer
Chapter 3: Describing Bivariate Data
	Introduction
	3.1 Describing Bivariate Categorical Data
	3.2 Describing Bivariate Quantitative Data
	Chapter Review
	Technology Today
	Reviewing What You've Learned
	Case Study: Are Your Clothes Really Clean?
Chapter 4: Probability
	Introduction
	4.1 Events and the Sample Space
	4.2 Calculating Probabilities Using Simple Events
	4.3 Useful Counting Rules
	4.4 Rules for Calculating Probabilities
	4.5 Bayes' Rule
	Chapter Review
	Reviewing What You've Learned
	Case Study: Probability and Decision Making in the Congo
Chapter 5: Discrete Probability Distributions
	5.1 Discrete Random Variables and Their Probability Distributions
	5.2 The Binomial Probability Distribution
	5.3 The Poisson Probability Distribution
	5.4 The Hypergeometric Probability Distribution
	Chapter Review
	Technology Today
	Reviewing What You've Learned
	Case Study: A Mystery: Cancers Near a Reactor
Chapter 6: The Normal Probability Distribution
	6.1 Probability Distributions for Continuous Random Variables
	6.2 The Normal Probability Distribution
	6.3 The Normal Approximation to the Binomial Probability Distribution
	Chapter Review
	Technology Today
	Reviewing What You've Learned
	Case Study: "Are You Going to Curve the Grades?"
Chapter 7: Sampling Distributions
	Introduction
	7.1 Sampling Plans and Experimental Designs
	7.2 Statistics and Sampling Distributions
	7.3 The Central Limit Theorem and the Sample Mean
	7.4 Assessing Normality
	7.5 The Sampling Distribution of the Sample Proportion
	7.6 A Sampling Application: Statistical Process Control (Optional)
	Chapter Review
	Technology Today
	Reviewing What You've Learned
	Case Study: Sampling the Roulette at Monte Carlo
Chapter 8: Large-Sample Estimation
	8.1 Where We've Been and Where We're Going
	8.2 Point Estimation
	8.3 Interval Estimation
	8.4 Estimating the Difference between Two Population Means
	8.5 Estimating the Difference between Two Binomial Proportions
	8.6 One-Sided Confidence Bounds
	8.7 Choosing the Sample Size
	Chapter Review
	Technology Today
	Reviewing What You've Learned
	Case Study: How Reliable Is That Poll? CBS News: How and Where America Eats
Chapter 9: Large-Sample Tests of Hypotheses
	Introduction
	9.1 A Statistical Test of Hypothesis
	9.2 A Large-Sample Test about a Population Mean
	9.3 A Large-Sample Test of Hypothesis for the Difference between Two Population Means
	9.4 A Large-Sample Test of Hypothesis for a Binomial Proportion
	9.5 A Large-Sample Test of Hypothesis for the Difference between Two Binomial Proportions
	9.6 Concluding Comments on Testing Hypotheses
	Chapter Review
	Technology Today
	Reviewing What You've Learned
	Case Study: An Aspirin a Day . . . ?
Chapter 10: Inference from Small Samples
	Introduction
	10.1 Student's t Distribution
	10.2 Small-Sample Inferences Concerning a Population Mean
	10.3 Small-Sample Inferences for the Difference between Two Population Means: Independent Random Samples
	10.4 Small-Sample Inferences for the Difference between Two Means: A Paired-­Difference Test
	10.5 Inferences Concerning a Population Variance
	10.6 Comparing Two Population Variances
	10.7 Revisiting the Small-Sample Assumptions
	Chapter Review
	Technology Today
	Reviewing What You've Learned
	Case Study: School Accountability-Are We Doing Better?
Chapter 11: The Analysis of Variance
	11.1 The Design of an Experiment
	11.2 The Completely Randomized Design: A One-Way Classification
	11.3 Ranking Population Means
	11.4 The Randomized Block Design: A Two-Way Classification
	11.5 The a x b Factorial Experiment: A Two-Way Classification
	11.6 Revisiting the Analysis of Variance Assumptions
	11.7 A Brief Summary
	Chapter Review
	Technology Today
	Reviewing What You've Learned
	Case Study: How to Save Money on Groceries!
Chapter 12: Simple Linear Regression and Correlation
	Introduction
	12.1 Simple Linear Regression
	12.2 An Analysis of Variance for Linear Regression
	12.3 Testing the Usefulness of the Linear Regression Model
	12.4 Diagnostic Tools for Checking the Regression Assumptions
	12.5 Estimation and Prediction Using the Fitted Line
	12.6 Correlation Analysis
	Chapter Review
	Technology Today
	Reviewing What You've Learned
	Case Study: Is Your Car "Made in the U.S.A."?
Chapter 13: Multiple Linear Regression Analysis
	Introduction
	13.1 The Multiple Regression Model
	13.2 Multiple Regression Analysis
	13.3 A Polynomial Regression Model
	13.4 Using Quantitative and Qualitative Predictor Variables in a Regression Model
	13.5 Testing Sets of Regression Coefficients
	13.6 Other Topics in Multiple Linear Regression
	13.7 Steps to Follow When Building a Multiple Regression Model
	Chapter Review
	Technology Today
	Reviewing What You've Learned
	Case Study: "Made in the U.S.A."-Another Look
Chapter 14: Analysis of Categorical Data
	14.1 The Multinomial Experiment and the Chi-Square Statistic
	14.2 Testing Specified Cell Probabilities: The Goodness-of-Fit Test
	14.3 Contingency Tables: A Two-Way Classification
	14.4 Comparing Several Multinomial Populations: A Two-Way Classification with Fixed Row or Column Totals
	14.5 Other Topics in Categorical Data Analysis
	Chapter Review
	Technology Today
	Reviewing What You've Learned
	Case Study: Who Is the Primary Breadwinner in Your Family?
Chapter 15: Nonparametric Statistics
	Introduction
	15.1 The Wilcoxon Rank Sum Test: Independent Random Samples
	15.2 The Sign Test for a Paired Experiment
	15.3 A Comparison of Statistical Tests
	15.4 The Wilcoxon Signed-Rank Test for a Paired Experiment
	15.5 The Kruskal-Wallis H-Test for Completely Randomized Designs
	15.6 The Friedman Fr-Test for Randomized Block Designs
	15.7 Rank Correlation Coefficient
	15.8 Summary
	Chapter Review
	Technology Today
	Reviewing What You've Learned
	Case Study: Amazon HQ2
Appendix I: Tables
Data Sources
Answers to Selected Exercises
Index