Real-World Statistics: In-Person Version
Edition: 4
Copyright: 2025
Edition: 4
Copyright: 2025
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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 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.