Real-World Statistics: In-Person Version

Author(s): Carol Saltsgaver

Edition: 4

Copyright: 2025

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ISBN 9798385158041

Details Ebook w/KHQ 180 days

Real-World Statistics was written for all college majors who have completed at least an intermediate algebra as well as a geometry course. The text contains many examples and exercises from a wide variety of statistical applications, making it appropriate for many different disciplines.

Real-World Statistics:

  • Exposes and engages students in introductory statistics using real data
  • Develops statistical literacy and critical thinking skills to help students better understand today’s data-driven world.

Real-World Statistics features:

  • Technology – specifically, the TI-83/84® series calculators.
  • Frequently Used Formulas – organized by chapter for quick reference.
  • Group Activities – incorporates concepts learned in each chapter.
  • Margin Notes – including Try-Its, Key Points, Reminders, and Calculator Steps.
  • Answers to Selected Exercises – all odd numbered exercises are given so students can check their comprehension of the material.

About the Author 
Preface 

PART 1: DESCRIPTIVE STATISTICS 

CHAPTER 1: Introduction to Statistics 
Section 1.1: Basic Statistical Definitions 
Section 1.2: Types of Data 
Section 1.3: Collecting Data 

CHAPTER 2: Summarizing and Graphing Data 
Section 2.1: Organizing Qualitative Data 
Section 2.2: Organizing Quantitative Data 
Section 2.3: Distribution Characteristics 
Section 2.4: Misrepresentation of Graphs 

CHAPTER 3: Numerically Summarizing Data 
Section 3.1: Measures of Center 
Section 3.2: Measures of Variation 
Section 3.3: Measures of Position 
Section 3.4: Constructing Boxplots 

CHAPTER 4: Probability 
Section 4.1: Basic Probability Rules 
Section 4.2: The Addition Rule 
Section 4.3: Multiplication Rule Basics 

CHAPTER 5: Probability Distributions 
Section 5.1: General Probability Distributions 
Section 5.2: Binomial Distributions 
Section 5.3: Mean and Standard Deviation: Binomial Distributions 

CHAPTER 6: The Normal Distribution
Section 6.1: Area and Probability 
Section 6.2: The Standard Normal Distribution 
Section 6.3: Normal Distributions 

PART 2: INFERENTIAL STATISTICS 

CHAPTER 7: Confidence Intervals and Sample Sizes 
Section 7.1: Sampling Distributions: Mean 
Section 7.2: Sampling Distributions: Proportion 
Section 7.3: Confidence Intervals for Population Means 
Section 7.4: Confidence Intervals for Population Proportions and Sample Size 

CHAPTER 8: Hypothesis Testing: Mean and Proportion 
Section 8.1: Basics of Hypothesis Testing 
Section 8.2: Hypothesis Testing: Population Means
Section 8.3: Hypothesis Testing: Population Proportions 

CHAPTER 9: Inferences: Two Populations 
Section 9.1: Inferences about Two Population Proportions 
Section 9.2: Inferences about Two Population Means: Independent Samples 
Section 9.3: Inferences about Two Population Means: Dependent Samples 

CHAPTER 10: Correlation and Regression 
Section 10.1: Scatterplots and Correlation 
Section 10.2: Hypothesis Testing for Correlation 
Section 10.3: Linear Regression 

Appendix: Distribution Tables 
Answers to Odd-Numbered Exercises 
Frequently Used Formulas 
Index

Carol Saltsgaver

Carol Saltsgaver has a BA in mathematics from Cameron University and an MS in mathematics from the University of Oklahoma. After teaching as a graduate student, she moved to the corporate world as an actuarial and marketing analyst in the Dallas area for a few years. She then went back to teaching and is now a clinical instructor in the Department of Mathematical Sciences at the University of Illinois at Springfield. She has taught many different courses including remedial mathematics courses, college algebra, quantitative reasoning, trigonometry, statistics, business calculus, and discrete mathematics. In addition, she has taught many of these courses online. While an educator in Oklahoma and Texas, she instructed not only remedial mathematics students, but also high-performing high school students at a math and science high school program.

Currently, she lives in Springfield, Illinois with her husband and many cats. She has two daughters and a grandson.

Real-World Statistics was written for all college majors who have completed at least an intermediate algebra as well as a geometry course. The text contains many examples and exercises from a wide variety of statistical applications, making it appropriate for many different disciplines.

Real-World Statistics:

  • Exposes and engages students in introductory statistics using real data
  • Develops statistical literacy and critical thinking skills to help students better understand today’s data-driven world.

Real-World Statistics features:

  • Technology – specifically, the TI-83/84® series calculators.
  • Frequently Used Formulas – organized by chapter for quick reference.
  • Group Activities – incorporates concepts learned in each chapter.
  • Margin Notes – including Try-Its, Key Points, Reminders, and Calculator Steps.
  • Answers to Selected Exercises – all odd numbered exercises are given so students can check their comprehension of the material.

About the Author 
Preface 

PART 1: DESCRIPTIVE STATISTICS 

CHAPTER 1: Introduction to Statistics 
Section 1.1: Basic Statistical Definitions 
Section 1.2: Types of Data 
Section 1.3: Collecting Data 

CHAPTER 2: Summarizing and Graphing Data 
Section 2.1: Organizing Qualitative Data 
Section 2.2: Organizing Quantitative Data 
Section 2.3: Distribution Characteristics 
Section 2.4: Misrepresentation of Graphs 

CHAPTER 3: Numerically Summarizing Data 
Section 3.1: Measures of Center 
Section 3.2: Measures of Variation 
Section 3.3: Measures of Position 
Section 3.4: Constructing Boxplots 

CHAPTER 4: Probability 
Section 4.1: Basic Probability Rules 
Section 4.2: The Addition Rule 
Section 4.3: Multiplication Rule Basics 

CHAPTER 5: Probability Distributions 
Section 5.1: General Probability Distributions 
Section 5.2: Binomial Distributions 
Section 5.3: Mean and Standard Deviation: Binomial Distributions 

CHAPTER 6: The Normal Distribution
Section 6.1: Area and Probability 
Section 6.2: The Standard Normal Distribution 
Section 6.3: Normal Distributions 

PART 2: INFERENTIAL STATISTICS 

CHAPTER 7: Confidence Intervals and Sample Sizes 
Section 7.1: Sampling Distributions: Mean 
Section 7.2: Sampling Distributions: Proportion 
Section 7.3: Confidence Intervals for Population Means 
Section 7.4: Confidence Intervals for Population Proportions and Sample Size 

CHAPTER 8: Hypothesis Testing: Mean and Proportion 
Section 8.1: Basics of Hypothesis Testing 
Section 8.2: Hypothesis Testing: Population Means
Section 8.3: Hypothesis Testing: Population Proportions 

CHAPTER 9: Inferences: Two Populations 
Section 9.1: Inferences about Two Population Proportions 
Section 9.2: Inferences about Two Population Means: Independent Samples 
Section 9.3: Inferences about Two Population Means: Dependent Samples 

CHAPTER 10: Correlation and Regression 
Section 10.1: Scatterplots and Correlation 
Section 10.2: Hypothesis Testing for Correlation 
Section 10.3: Linear Regression 

Appendix: Distribution Tables 
Answers to Odd-Numbered Exercises 
Frequently Used Formulas 
Index

Carol Saltsgaver

Carol Saltsgaver has a BA in mathematics from Cameron University and an MS in mathematics from the University of Oklahoma. After teaching as a graduate student, she moved to the corporate world as an actuarial and marketing analyst in the Dallas area for a few years. She then went back to teaching and is now a clinical instructor in the Department of Mathematical Sciences at the University of Illinois at Springfield. She has taught many different courses including remedial mathematics courses, college algebra, quantitative reasoning, trigonometry, statistics, business calculus, and discrete mathematics. In addition, she has taught many of these courses online. While an educator in Oklahoma and Texas, she instructed not only remedial mathematics students, but also high-performing high school students at a math and science high school program.

Currently, she lives in Springfield, Illinois with her husband and many cats. She has two daughters and a grandson.