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Seeing Through Statistics

By Jessica M. Utts

5th Edition © 2025
Discipline:Statistics
Course:Intro Probability & Statistics
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Utts's SEEING THROUGH STATISTICS, 5th Edition, helps students discover the impact the science of statistics has on their lives and prepares them to make better decisions when faced with uncertainty. Emphasizing ideas instead of computations, Utts develops statistical literacy and critical thinking skills through engaging, real-world applications. The text highlights the key concepts that educated citizens need to know about statistics. Revisions to the fifth edition focus on currency, inclusivity, relevancy and the online experience. WebAssign reinforces understanding and includes the Statistical Analysis and Learning Tool (SALT), which enables students to analyze and visualize data without getting bogged down in complex computations.

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About this product

Utts's SEEING THROUGH STATISTICS, 5th Edition, helps students discover the impact the science of statistics has on their lives and prepares them to make better decisions when faced with uncertainty. Emphasizing ideas instead of computations, Utts develops statistical literacy and critical thinking skills through engaging, real-world applications. The text highlights the key concepts that educated citizens need to know about statistics. Revisions to the fifth edition focus on currency, inclusivity, relevancy and the online experience. WebAssign reinforces understanding and includes the Statistical Analysis and Learning Tool (SALT), which enables students to analyze and visualize data without getting bogged down in complex computations.

Table of contents

Chapters

Cover Page
Title Page
Copyright Page
Dedication
About the Author
Preface
Acknowledgments
Part 1. Finding Data in Life
Part 2. Finding Life in Data
Part 3. Understanding Uncertainty in Life
Part 4. Making Judgments from Surveys and Experiments
Contents of the Appendix and Companion Website
Appendix of News Stories
Show more

Part 1. Finding Data in Life

Chapter 1. The Benefits and Risks of Using Statistics
Preview this section ↗
1.1. Why Bother Reading This Book? ↗
1.2. What Is Statistics All About? ↗
1.3. Detecting Patterns and Relationships ↗
How to Move from Noticing to Knowing ↗
1.4. Don’t Be Deceived by Improper Use of Statistics ↗
1.5. Summary and Conclusions ↗
Thinking About Key Concepts. ↗
Reflection Questions ↗
Exercises ↗
Mini-Projects ↗
References ↗
Chapter 2. Reading the News
2.1. The Educated Consumer of Data
What Are Data?
Don’t Always Believe What You Read
2.2. Origins of News Stories
News from Academic Conferences
News from Published Reports
2.3. How to Be a Statistics Sleuth: Seven Critical Components
2.4. Four Hypothetical Examples of Bad Reports
2.5. Planning Your Own Study: Defining the Components in Advance
Thinking About Key Concepts.
Reflection Questions
Exercises
Mini-Projects
References
Chapter 3. Measurements, Mistakes, and Misunderstandings
3.1. Simple Measures Don’t Exist
3.2. It’s All in the Wording
Deliberate Bias
Unintentional Bias
Desire to Please
Asking the Uninformed
Unnecessary Complexity
Ordering of Questions
Confidentiality Versus Anonymity
3.3. Open or Closed Questions: Should Choices Be Given?
Advantages and Disadvantages of Open Questions
Advantages and Disadvantages of Closed Form Questions
Pilot Studies and Pilot Surveys
3.4. Defining What Is Being Measured
Some Concepts Are Hard to Define Precisely
Measuring Attitudes and Emotions
3.5. Defining a Common Language
Categorical Versus Measurement Variables
Continuous Versus Discrete Measurement Variables
Validity, Reliability, and Bias
Variability Across Measurements
Understanding Natural Variability Is the Key to Understanding Statistics
Thinking About Key Concepts.
Reflection Questions
Exercises
Mini-Projects
References
Chapter 4. How to Get a Good Sample
4.1. Common Research Strategies
Sample Surveys
Randomized Experiments
Observational Studies
Meta-Analyses
Case Studies
4.2. Defining a Common Language
4.3. The Beauty of Sampling
Accuracy of a Sample Survey: Margin of Error
Other Advantages of Sample Surveys
4.4. Simple Random Sampling
4.5. Other Sampling Methods
Stratified Random Sampling
Cluster Sampling
Systematic Sampling
Random Digit Dialing
Internet Panel Sampling
Multistage Sampling
4.6. Difficulties and Disasters in Sampling
Difficulties in Sampling
Disasters in Sampling
Thinking About Key Concepts
Reflection Questions
Exercises
Mini-Projects
References
Chapter 5. Experiments and Observational Studies
5.1. Defining a Common Language
Explanatory Variables, Response Variables, and Treatments
Randomized Experiments Versus Observational Studies
Confounding Variables and Interacting Variables
Experimental Units, Subjects, and Volunteers
5.2. Designing a Good Experiment
Randomization: The Fundamental Feature of Experiments
Control Groups, Placebos, and Blinding
Matched Pairs, Blocks, and Repeated Measures
5.3. Difficulties and Disasters in Experiments
Confounding Variables
Interacting Variables
Placebo, Hawthorne, and Experimenter Effects
Lack of Ecological Validity and Consequent Generalization
5.4. Designing a Good Observational Study
Types of Observational Studies
Advantages of Case-Control Studies
5.5. Difficulties and Disasters in Observational Studies
Confounding Variables and the Implications of Causation
Extending the Results Inappropriately
Using the Past as a Source of Data
5.6. Random Sample Versus Random Assignment
Extending Results to a Larger Population: Random Sampling
Establishing Cause and Effect: Random Assignment
Thinking About Key Concepts
Reflection Questions
Exercises
Mini-Projects
References
Chapter 6. Getting the Big Picture
6.1. Final Questions
Reflection Questions
Mini-Projects
References

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