Neil J Salkind, Bruce B Frey, Susan Parault Dowds
Study Guide for Education to Accompany Salkind and Frey′s Statistics for People Who (Think They) Hate Statistics
Neil J Salkind, Bruce B Frey, Susan Parault Dowds
Study Guide for Education to Accompany Salkind and Frey′s Statistics for People Who (Think They) Hate Statistics
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This Study Guide for introductory statistics courses in education departments is designed to accompany Neil J. Salkind and Bruce B. Frey's best-selling Statistics for People Who (Think They) Hate Statistics, Seventh Edition. Extra exercises; activities; and true/false, multiple choice, and essay questions (with answers to all questions) feature education-specific content to help further student mastery of text concepts. A dataset is provided for use with the book.
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This Study Guide for introductory statistics courses in education departments is designed to accompany Neil J. Salkind and Bruce B. Frey's best-selling Statistics for People Who (Think They) Hate Statistics, Seventh Edition. Extra exercises; activities; and true/false, multiple choice, and essay questions (with answers to all questions) feature education-specific content to help further student mastery of text concepts. A dataset is provided for use with the book.
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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Repro India Limited
- 7th edition
- Seitenzahl: 176
- Erscheinungstermin: 4. September 2019
- Englisch
- Abmessung: 279mm x 218mm x 12mm
- Gewicht: 424g
- ISBN-13: 9781544395975
- ISBN-10: 1544395973
- Artikelnr.: 57119667
- Verlag: Repro India Limited
- 7th edition
- Seitenzahl: 176
- Erscheinungstermin: 4. September 2019
- Englisch
- Abmessung: 279mm x 218mm x 12mm
- Gewicht: 424g
- ISBN-13: 9781544395975
- ISBN-10: 1544395973
- Artikelnr.: 57119667
Neil J. Salkind received his PhD in human development from the University of Maryland, and after teaching for 35 years at the University of Kansas, he was Professor Emeritus in the Department of Psychology and Research in Education, where he collaborated with colleagues and work with students. His early interests were in the area of children's cognitive development, and after research in the areas of cognitive style and (what was then known as) hyperactivity, he was a postdoctoral fellow at the University of North Carolina's Bush Center for Child and Family Policy. His work then changed direction to focus on child and family policy, specifically the impact of alternative forms of public support on various child and family outcomes. He delivered more than 150 professional papers and presentations; written more than 100 trade and textbooks; and is the author of Statistics for People Who (Think They) Hate Statistics (SAGE), Theories of Human Development (SAGE), and Exploring Research (Prentice Hall). He has edited several encyclopedias, including the Encyclopedia of Human Development, the Encyclopedia of Measurement and Statistics, and the Encyclopedia of Research Design. He was editor of Child Development Abstracts and Bibliography for 13 years. He lived in Lawrence, Kansas, where he liked to read, swim with the River City Sharks, work as the proprietor and sole employee of big boy press, bake brownies (see www.statisticsforpeople.com for the recipe), and poke around old Volvos and old houses.
Chapter 1. Statistics or Sadistics? It's Up to You
Chapter 2. Computing and Understanding Averages: Means to an End
Chapter 3. Understanding Variability: Vivé la Différence
Chapter 4. Creating Graphs: A Picture Really Is Worth a Thousand Words
Chapter 5. Computing Correlation Coefficients: Ice Cream and Crime
Chapter 6. An Introduction to Understanding Reliability and Validity: Just
the Truth
Chapter 7. Hypotheticals and You: Testing Your Questions
Chapter 8. Probability and Why it Counts: Fun with a Bell-Shaped Curve
Chapter 9. Significantly Significant: What It Means for You and Me
Chapter 10. The One-Sample Z-Test: Only the Lonely
Chapter 11. t(ea) for Two: Tests Between the Means of Different Groups
Chapter 12. t(ea) for Two (Again): Tests Between the Means of Related
Groups
Chapter 13. Two Groups Too Many? Try Analysis of Variance
Chapter 14. Two Too Many Factors: Factorial Analysis of Variance-A Brief
Introduction
Chapter 15. Testing Relationships Using the Correlation Coefficient:
Cousins or Just Good Friends?
Chapter 16. Using Linear Regression: Predicting the Future
Chapter 17. Chi-Square and Some Other Nonparametric Tests: What to Do When
You're Not Normal
Chapter 18. Some Other (Important) Statistical Procedures You Should Know
About
Chapter 19. Data Mining: An Introduction to Getting the Most Out of Your
BIG Data
Chapter 2. Computing and Understanding Averages: Means to an End
Chapter 3. Understanding Variability: Vivé la Différence
Chapter 4. Creating Graphs: A Picture Really Is Worth a Thousand Words
Chapter 5. Computing Correlation Coefficients: Ice Cream and Crime
Chapter 6. An Introduction to Understanding Reliability and Validity: Just
the Truth
Chapter 7. Hypotheticals and You: Testing Your Questions
Chapter 8. Probability and Why it Counts: Fun with a Bell-Shaped Curve
Chapter 9. Significantly Significant: What It Means for You and Me
Chapter 10. The One-Sample Z-Test: Only the Lonely
Chapter 11. t(ea) for Two: Tests Between the Means of Different Groups
Chapter 12. t(ea) for Two (Again): Tests Between the Means of Related
Groups
Chapter 13. Two Groups Too Many? Try Analysis of Variance
Chapter 14. Two Too Many Factors: Factorial Analysis of Variance-A Brief
Introduction
Chapter 15. Testing Relationships Using the Correlation Coefficient:
Cousins or Just Good Friends?
Chapter 16. Using Linear Regression: Predicting the Future
Chapter 17. Chi-Square and Some Other Nonparametric Tests: What to Do When
You're Not Normal
Chapter 18. Some Other (Important) Statistical Procedures You Should Know
About
Chapter 19. Data Mining: An Introduction to Getting the Most Out of Your
BIG Data
Chapter 1. Statistics or Sadistics? It's Up to You
Chapter 2. Computing and Understanding Averages: Means to an End
Chapter 3. Understanding Variability: Vivé la Différence
Chapter 4. Creating Graphs: A Picture Really Is Worth a Thousand Words
Chapter 5. Computing Correlation Coefficients: Ice Cream and Crime
Chapter 6. An Introduction to Understanding Reliability and Validity: Just
the Truth
Chapter 7. Hypotheticals and You: Testing Your Questions
Chapter 8. Probability and Why it Counts: Fun with a Bell-Shaped Curve
Chapter 9. Significantly Significant: What It Means for You and Me
Chapter 10. The One-Sample Z-Test: Only the Lonely
Chapter 11. t(ea) for Two: Tests Between the Means of Different Groups
Chapter 12. t(ea) for Two (Again): Tests Between the Means of Related
Groups
Chapter 13. Two Groups Too Many? Try Analysis of Variance
Chapter 14. Two Too Many Factors: Factorial Analysis of Variance-A Brief
Introduction
Chapter 15. Testing Relationships Using the Correlation Coefficient:
Cousins or Just Good Friends?
Chapter 16. Using Linear Regression: Predicting the Future
Chapter 17. Chi-Square and Some Other Nonparametric Tests: What to Do When
You're Not Normal
Chapter 18. Some Other (Important) Statistical Procedures You Should Know
About
Chapter 19. Data Mining: An Introduction to Getting the Most Out of Your
BIG Data
Chapter 2. Computing and Understanding Averages: Means to an End
Chapter 3. Understanding Variability: Vivé la Différence
Chapter 4. Creating Graphs: A Picture Really Is Worth a Thousand Words
Chapter 5. Computing Correlation Coefficients: Ice Cream and Crime
Chapter 6. An Introduction to Understanding Reliability and Validity: Just
the Truth
Chapter 7. Hypotheticals and You: Testing Your Questions
Chapter 8. Probability and Why it Counts: Fun with a Bell-Shaped Curve
Chapter 9. Significantly Significant: What It Means for You and Me
Chapter 10. The One-Sample Z-Test: Only the Lonely
Chapter 11. t(ea) for Two: Tests Between the Means of Different Groups
Chapter 12. t(ea) for Two (Again): Tests Between the Means of Related
Groups
Chapter 13. Two Groups Too Many? Try Analysis of Variance
Chapter 14. Two Too Many Factors: Factorial Analysis of Variance-A Brief
Introduction
Chapter 15. Testing Relationships Using the Correlation Coefficient:
Cousins or Just Good Friends?
Chapter 16. Using Linear Regression: Predicting the Future
Chapter 17. Chi-Square and Some Other Nonparametric Tests: What to Do When
You're Not Normal
Chapter 18. Some Other (Important) Statistical Procedures You Should Know
About
Chapter 19. Data Mining: An Introduction to Getting the Most Out of Your
BIG Data