Introduction to probability and statistics

✍ Scribed by William Mendenhall; Barbara M. Beaver; Robert J. Beaver

• Year: 2020
• Tongue: English
• Leaves: 788
• Edition: 15
• Category: Library

✦ Table of Contents

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