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An Introduction to Statistics
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An Introduction to Statistics
An Active Learning Approach

Third Edition


January 2021 | 512 pages | SAGE Publications, Inc
This updated and reorganized Third Edition of this textbook takes a workbook-style approach that encourages an active approach to learning statistics. Carefully placed reading questions throughout each chapter allow students to apply their knowledge right away, while in-depth activities based on current behavioral science scenarios, each with problem sets and quiz questions, give students the opportunity to assess their understanding of concepts while reading detailed explanations of more complex statistical concepts. Additional practice problems further solidify student learning. Most activities are self-correcting, so if a concept is misunderstood, this misunderstanding is corrected early in the learning process. After working through each chapter, students are far more likely to understand the material than when they only read the material.

 
Preface
 
Acknowledgments
 
About the Authors
 
Part 1: Descriptive Statistics and Sampling Error
 
Chapter 1: Introduction to Statistics and Frequency Distributions
How to Be Successful in This Course

 
Math Skills Required in This Course

 
Statistical Software Options

 
Why Do You Have to Take Statistics?

 
The Four Pillars of Scientific Reasoning

 
Populations and Samples

 
Independent and Dependent Variables

 
Identify How a Variable Is Measured

 
Graphing Data

 
Shapes of Distributions

 
Frequency Distribution Tables

 
 
Chapter 2: Central Tendency and Variability
Frequency Distribution Graphs and Tables

 
Central Tendency: Choosing Mean, Median, or Mode

 
Computing Measures of Central Tendency

 
Variability: Range or Standard Deviation

 
Steps in Computing a Population’s Standard Deviation

 
Steps in Computing a Sample’s Standard Deviation

 
Constructing a Scientific Conclusion

 
 
Chapter 3: z scores
Computing and Interpreting z for a Raw Score

 
Finding Raw Score “Cut Lines”

 
Finding the Probability of z Scores Using the Standard Normal Curve

 
Positive z Score Example

 
Negative z Score Example

 
Proportion Between Two z Scores Example

 
 
Chapter 4: Sampling Error and Confidence Intervals with z and t Distributions
Sampling and Sampling Error

 
The Central Limit Theorem and the Standard Error of the Mean (SEM)

 
Applying the SEM to Find Statistical Evidence

 
 
Part 2: Applying the Four Pillars of Scientific Reasoning to Mean Differences
 
Chapter 5: Single sample t, effect sizes, and confidence intervals
Four Pillars of Scientific Reasoning

 
Apply the Four Pillars of Scientific Reasoning

 
Construct a Well-Supported Scientific Conclusion

 
 
Chapter 6: Related samples t, effect sizes, and confidence intervals
Related Samples t Test

 
Logic of the Single Sample and Related Samples t Tests

 
Apply the Four Pillars of Scientific Reasoning

 
Construct a Well-Supported Scientific Conclusion

 
 
Chapter 7: Independent samples t, effect sizes, and confidence intervals
When to Use the Three t Tests

 
The t Test Logic and the Independent Samples t Formula

 
Apply the Four Pillars of Scientific Reasoning

 
Construct a Well-Supported Scientific Conclusion

 
How to Interpret High p Values

 
 
Chapter 8: One-way ANOVA, effect sizes, and confidence intervals
Independent Samples One-Way ANOVA

 
Logic of the ANOVA

 
Apply Four Pillars of Scientific Reasoning

 
 
Chapter 9: Two-way ANOVA, effect sizes, and confidence intervals
Purpose of Two-Way ANOVA

 
Logic of Two-Way ANOVA

 
Apply Four Pillars of Scientific Reasoning

 
 
Part 3: Applying the Four Pillars of Scientific Reasoning to Associations
 
Chapter 10: Correlations, effect sizes, and confidence intervals
When to Use Correlations

 
The Logic of Correlation

 
Interpreting Correlation Coefficients

 
Spearman’s (rs) Correlation

 
Correlation Does Not Equal Causation: True but Misleading

 
Apply the Four Pillars of Scientific Reasoning

 
Construct a Well-Supported Scientific Conclusion

 
 
Chapter 11: Chi square and effect sizes
When to Use X2 Statistics

 
Logic of the X2 Test

 
Apply the Pillars of Scientific Reasoning

 
Construct a Well-Supported Scientific Conclusion

 
Apply the Pillars of Scientific Reasoning: X2 for Independence

 
Appendices

 
References

 
Index

 

Supplements

Instructor Resource Site
edge.sagepub.com/carlson3e

For additional information, custom options, or to request a personalized walkthrough of these resources, please contact your sales representative.


LMS cartridge included with this title for use in Blackboard, Canvas, Brightspace by Desire2Learn (D2L), and Moodle

The LMS cartridge makes it easy to import this title’s instructor resources into your learning management system (LMS). These resources include:
  • Test bank
  • Editable chapter-specific PowerPoint® slides
  • Answers to the textbook’s Reading Questions
  • Answers to the textbook’s Activity Questions
  • Additional Practice Tests and Answers
  • All tables and figures from the textbook
Don’t use an LMS platform?

You can still access all of the same online resources for this title via the password-protected Instructor Resource Site.
Student study site
edge.sagepub.com/carlson3e

The open-access Student Study Site makes it easy for students to maximize their study time, anywhere, anytime. It offers flashcards that strengthen understanding of key terms and concepts, as well as learning objectives that reinforce the most important material.
Key features
NEW TO THIS EDITION:
  • More emphasis on interpreting statistics. New coverage of “4 Pillars of Scientific Reasoning” (Hypothesis Testing with a Continuous p value, Practical Importance with Effect Size, Population Estimation with Confidence Intervals, and Methodology and Scientific Literature) helps students think about statistical results and create well-supported scientific conclusions,
  • Enhanced activity questions. Most enhanced questions now use a fixed-choice format to provide better feedback to students to help them identify areas of improvement.
  • A new emphasis on interpreting p values continuously rather than dichotomously (i.e., using critical value cut offs) follows an approach advised by most statisticians.
  • More software options (including free, simple-to-use JASP and jamovi) as well as SPSS are supported. Instructors can also use this textbook with any statistics program they prefer.
  • A streamlined organization with fewer chapters covers the same topics in more depth by combining central tendency and variability into a single chapter, integrating confidence intervals into multiple chapters, and introducing hypothesis testing with single sample t rather than z for a sample mean.
  • Expanded coverage of effect sizes includes all pairwise comparisons (including ANOVAs).
  • More instruction on writing results using APA style, particularly in the t-test and ANOVA chapters, gives readers confidence to convey their data.
  • Integrative assignments in the related t, independent t, one-way ANOVA, and correlation chapters reinforce the different information researchers obtain from significance tests, effect sizes, and confidence intervals, encouraging students to think like researchers.
  • A new textbook website contains useful resources for students and instructors, including answer keys for the activities, practice tests for each chapter, instructions for using SPSS, JASP, and jamovi, data files for all activities in the book, a test bank, and lecture slides.
KEY FEATURES:
  • Embedded reading questions and empirically developed activities in each chapter help students extract key concepts and enable them to learn by doing.
  • Carefully developed scenarios, problem sets, and quiz questions in each chapter help students test their knowledge and master the material.
  • A decision tree at the end of the book helps students choose the correct statistical tool for hypothesis testing.

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