Statistics and Probability with Applications (High School) by Daren Starnes; Josh Tabor; Luke Wilcox - Fourth Edition, 2021 from Macmillan Student Store

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Statistics and Probability with Applications (High School)

Fourth  Edition©2021  Daren Starnes; Josh Tabor; Luke Wilcox

About

Table of Contents

About the Authors 
Acknowledgments
To the Student 

Chapter 1 Analyzing One-Variable Data    
Lesson 1.1 Statistics: The Science and Art of Data    
Lesson 1.2 Displaying Categorical Data      
Lesson 1.3 Displaying Quantitative Data: Dotplots    
Lesson 1.4 Displaying Quantitative Data: Stemplots    
Lesson 1.5 Displaying Quantitative Data: Histograms    
Lesson 1.6 Measuring Center       
Lesson 1.7 Measuring Variability       
Lesson 1.8 Summarizing Quantitative Data: Boxplots and Outliers  

Chapter 2 Modeling One-Variable  Quantitative Data 
Lesson 2.1  Describing Location in a Distribution     
Lesson 2.2 Transforming Data       
Lesson 2.3 Density Curves and the Normal Distribution    
Lesson 2.4 The Empirical Rule and Assessing Normality   
Lesson 2.5 Normal Distributions: Finding Areas from Values    
Lesson 2.6 Normal Distributions: Finding Values from Areas   

Chapter 3 Analyzing Two-Variable Data 
Lesson 3.1 Relationships Between Two Categorical Variables
Lesson 3.2 Relationships Between Two Quantitative Variables
Lesson 3.3 Correlation
Lesson 3.4 More about Correlation
Lesson 3.5 Regression Lines
Lesson 3.6 The Least-Squares Regression Line
Lesson 3.7 Assessing a Regression Model

Chapter 4 Collecting Data 
Lesson 4.1 Introduction to Data Collection
Lesson 4.2 Sampling: Good and Bad
Lesson 4.3 Sampling and Surveys
Lesson 4.4 Inference for Sampling
Lesson 4.5 Observational Studies and Experiments
Lesson 4.6 How to Experiment Well
Lesson 4.7 Inference for Experiments
Lesson 4.8 Using Studies Wisely

Chapter 5 Probability
Lesson 5.1 Randomness, Probability, and Simulation
Lesson 5.2 Basic Probability Rules
Lesson 5.3 Two-Way Tables and Venn Diagrams
Lesson 5.4 Conditional Probability and Independence
Lesson 5.5 The General Multiplication Rule and Tree Diagrams
Lesson 5.6 The Multiplication Rule for Independent Events
Lesson 5.7 The Multiplication Counting Principle and Permutations
Lesson 5.8 Combinations and Probability

Chapter 6 Random Variables 
Lesson 6.1 Two Types of Random Variables
Lesson 6.2 Analyzing Discrete Random Variables
Lesson 6.3 Binomial Random Variables
Lesson 6.4 Analyzing Binomial Random Variables
Lesson 6.5 Normal Approximation to Binomial Distributions

Chapter 7 Sampling Distributions 
Lesson 7.1 What Is a Sampling Distribution?
Lesson 7.2 Sampling Distributions: Center and Variability
Lesson 7.3  The Sampling Distribution of a Sample Proportion
Lesson 7.4 The Sampling Distribution of a Sample Mean
Lesson 7.5 The Central Limit Theorem

Chapter 8 Estimating a Parameter 
Lesson 8.1 The Idea of a Confidence Interval
Lesson 8.2 What Affects the Margin of Error?
Lesson 8.3 Estimating a Proportion
Lesson 8.4 Confidence Intervals for a Proportion
Lesson 8.5 Estimating a Mean
Lesson 8.6 Confidence Intervals for a Mean

Chapter 9 Testing a Claim 
Lesson 9.1 The Idea of a Significance Test
Lesson 9.2 Significance Tests and Decision Making
Lesson 9.3 Testing a Claim about a Proportion
Lesson 9.4 Significance Tests for a Proportion
Lesson 9.5 Testing a Claim about a Mean
Lesson 9.6 Significance Tests for a Mean

Chapter 10 Comparing Two Populations or Treatments 
Lesson 10.1 Estimating a Difference Between Two Proportions
Lesson 10.2 Testing a Claim about a Difference Between Two Proportions
Lesson 10.3 Estimating a Difference Between Two Means
Lesson 10.4 Testing a Claim about a Difference Between Two Means
Lesson 10.5 Paired Data: Estimating a Mean Difference
Lesson 10.6 Paired Data: Testing a Claim about a Mean Difference

Chapter 11 Inference for Distributions and Relationships 
Lesson 11.1 Testing the Distribution of a Categorical Variable
Lesson 11.2 Chi-Square Tests for Goodness of Fit
Lesson 11.3 Testing the Relationship Between Two Categorical Variables
Lesson 11.4 Chi-Square Tests for Association
Lesson 11.5 Estimating the Slope of a Least-Squares Regression Line
Lesson 11.6 Testing a Claim about the Slope of a Least-Squares Regression Line

Solutions
Glossary/Glosario
Notes and Data Sources
Index
Table A Standard Normal Probabilities
Table B t Distribution Critical Values
Table C Chi-Square Distribution Critical Values
Table D Random Digits

Daren S. Starnes

Daren S. Starnes is Mathematics Department Chair and holds the Robert S. and Christina Seix Dow Distinguished Master Teacher Chair in Mathematics at The Lawrenceville School near Princeton, New Jersey. He earned his MA in Mathematics from the University of Michigan and his BS in Mathematics from the University of North Carolina at Charlotte. Daren is also an alumnus of the North Carolina School of Science and Mathematics. Daren has led numerous one-day and weeklong AP® Statistics institutes for new and experienced teachers, and he has been a Reader, Table Leader, and Question Leader for the AP® Statistics exam since 1998. Daren is a frequent speaker at local, state, regional, national, and international conferences. He has written articles for The Mathematics Teacher and CHANCE magazine. From 2004 to 2009, Daren served on the ASA/NCTM Joint Committee on the Curriculum in Statistics and Probability (which he chaired in 2009). While on the committee, he edited the Guidelines for Assessment and Instruction in Statistics Education (GAISE) pre-K–12 report and coauthored (with Roxy Peck) Making Sense of Statistical Studies, a capstone module in statistical thinking for high school students. Daren is also coauthor of the popular on-level text Statistics and Probability with Applications.

Josh Tabor

Josh Tabor has enjoyed teaching on-level and AP® Statistics to high school students for more than 23 years, most recently at his alma mater, Canyon del Oro High School in Oro Valley, Arizona. He received a BS in Mathematics from Biola University, in La Mirada, California. In recognition of his outstanding work as an educator, Josh was named one of the five finalists for Arizona Teacher of the Year in 2011. He is a past member of the AP® Statistics Development Committee (2005–2009) and has been a Reader, Table Leader, and Question Leader at the AP® Statistics Reading since 1999. In 2013, Josh was named to the SAT® Mathematics Development Committee. Each year, Josh leads one-week AP® Summer Institutes and College Board workshops around the world and frequently speaks at local, national, and international conferences. In addition to teaching and speaking, Josh has published articles in The American Statistician, The Mathematics Teacher, STATS Magazine, and The Journal of Statistics Education. He is the coauthor with Daren Starnes of two other popular statistics textbooks, The Practice of Statistics for the AP® Exam, Sixth Edition, and Statistics and Probability with Applications, Third Edition, for on-level statistics. Outside of work, Josh enjoys gardening, traveling, and playing board games with his family.

Luke Wilcox

Luke Wilcox is a National Board Certified teacher who has spent his 20-year teaching career at East Kentwood High School, the most diverse public high school in the state of Michigan. His teaching as been recognized with the 2013 Presidential Award and the 2018 Michigan Teacher of the Year award, each giving him the opportunity to visit the White House to meet the president. Luke is the author of the Annotated Teacher’s Edition for The Practice of Statistics, where he offers valuable insights gathered from his own classroom teaching experiences, as well as from his participation as a Reader and Table Leader at the AP® Statistics Reading. Luke also supports teachers through a variety of in-person and online workshops, as well as being a frequent presenter at conferences. To further help statistics teachers, Luke co-developed the website statsmedic.com, which is positively transforming statistics instruction in classrooms around the country. Luke leads his students with an Experience First, Formalize Later approach to teaching statistics—in which students engage in the mathematical thinking and reasoning before being provided algorithmic formulas and definitions. In his spare time, Luke enjoys traveling with his wife and two kids, running, and eating tacos.