Statistics and Probability with Applications (High School) by Daren Starnes; Josh Tabor - Third Edition, 2017 from Macmillan Student Store

Statistics and Probability with Applications (High School)

Third  Edition©2017  Daren Starnes; Josh Tabor

About

Written directly for high school students, by those who understand the common struggles of the course the most (your teachers!), Statistics and Probability with Applications strives to make learning engaging enough to keep you on track in the course. Through lively real-life examples, you'll learn how you can use statistics in your future academic endeavors as well as any career out there.

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

Daren S. Starnes

Daren Starnes has taught a variety of statistics courses — including Introductory Statistics, AP® Statistics, and Mathematical Statistics — for 25 years. 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 has been a Reader, Table Leader, and Question Leader for the AP® Statistics exam for over 20 years. As a College Board consultant since 1999, Daren has led hundreds of workshops for AP® Statistics teachers throughout the United States and overseas. He frequently presents in-person and online sessions about statistics teaching and learning for high school and college faculty. Daren is an active member of the American Statistical Association (ASA), the National Council of Teachers of Mathematics (NCTM), the American Mathematical Association of Two-Year Colleges (AMATYC), and the International Association for Statistical Education (IASE). He served on the ASA/NCTM Joint Committee on the Curriculum in Statistics and Probability for six years. While on the committee, he edited the Guidelines for Assessment and Instruction in Statistics Education (GAISE) Report: A Pre-K–12 Curriculum Framework report. Daren is coauthor of The Practice of Statistics (now in its seventh edition), the best-selling textbook for AP® Statistics, and of Statistics and Probability with Applications (now in its fourth edition), a popular choice for high school introductory statistics. Daren and his wife Judy enjoy traveling, rambling walks, jigsaw puzzles, and spending time with their three sons and seven grandchildren.

Josh Tabor

Josh Tabor has enjoyed teaching Introductory and AP® Statistics for more than 26 years. 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 five finalists for Arizona Teacher of the Year in 2011. He is a past member of the AP® Statistics Development Committee (2005–2009), as well as an experienced Table Leader, Question Leader, and Exam Leader at the AP® Statistics Reading. In 2013, Josh was named to the SAT® Mathematics Development Committee. Josh is a member of the American Statistical Association (ASA) and was a reviewer for the ASA’s Pre-K–12 Guidelines for Assessment and Instruction in Statistics Education II (GAISE II). Each year, Josh leads many workshops and frequently speaks at local, national, and international conferences. In addition to teaching and speaking, he has authored articles in The American Statistician, The Mathematics Teacher, STATS Magazine, and The Journal of Statistics Education. Josh is coauthor of The Practice of Statistics (now in its seventh edition), the best-selling textbook for AP® Statistics, and of Statistics and Probability with Applications (now in its fourth edition), a popular choice for high school introductory statistics. Combining his love of statistics and sports, Josh teamed with Christine Franklin to write Statistical Reasoning in Sports, an innovative textbook for statistical literacy courses. Outside of work, Josh enjoys gardening, traveling, and playing board games with his family.