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Köp båda 2 för 1925 krNeil 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 childrens 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 Carolinas 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.
Leslie A. Shaw received her PhD in psychology from the University of Kansas, specifically in quantitative psychology. During graduate school, she worked on a variety of projects from university class enrollment, alumni donations, community policing, and self-determination. She also taught statistical computing labs and introductory statistics in a team-teaching format. The self-determination research led to more opportunities at the Beach Center on Disabilities and Kansas University Center on Developmental Disabilities to contribute to research on the Supports Intensity Scale, both adult and child versions, and the Self-Determination Inventory: Self Report. After graduation, she held a postdoctoral position at the Kansas University Center on Developmental Disabilities, where she also taught a class each semester in the quantitative psychology program. She is now a research associate at the Yang-Tan Institute on Employment and Disability in the ILR School at Cornell University. She has coauthored more than 20 articles to date, and she serves as a statistical consultant for the journal Intellectual and Developmental Disabilities.
Preface Acknowledgements About the Authors Part I Yippee! I'm in Statistics Chapter 1. Statistics or Sadistics? It's Up to You What You Will Learn in This Chapter Why Statistics? A 5-Minute History of Statistics Statistics: What it is and Isn't What am I doing in a Statistics Class? Ten Ways to Use this Book (and Learn Statistics at the Same Time) Key to Difficulty Icons Glossary Real-World Stats Summary Time to Practice Part II Welcome to the Interesting, Flexible, Useful, Fun and (Very) Deep Worlds of R and RStudio Chapter 2. Here's Why We Love R and How to Get Started What You Will Learn in This Chapter A Very Short History of R The Plusses of Using R Where to Find and Download R The Opening R Screen A Note About Formatting Bunches of Data - Free! Getting R Help Some Important Lingo RStudio Where to Find RStudio and How to Install It Ordering from RStudio Summary Time to Practice Chapter 3. Using RStudio: Much Easier Than You Think What You Will Learn in This Chapter Why RStudio (and Why Not Just R?) The Grand Tour and All About Those Four Panes RStudio Pane Goodies Showing Your Stuff - Working With Menus and Tabs and A Sample Data Analysis Using RStudio Working with Data Next Step: Using and Importing Datasets Reading in Established Datasets Computing Some Statistics Summary Time to Practice Part III Sigma Freud and Descriptive Statistics Chapter 4. Means to an End: Computing and Understanding Averages What You Will Learn in This Chapter What You Will Learn in This Chapter Computing the Mean Computing the Median Computing the Mode When to Use What Measure of Central Tendency (and All You Need to Know About Scales of Measurement for Now) Using the Computer to Compute Descriptive Statistics Real World Stats Summary Time to Practice Chapter 5. Understanding Variability: Vive la Difference What You Will Learn in This Chapter Why Understanding Variability is Important Computing the Range Computing the Standard Deviation Computing the Variance Using R to Compute Measures of Variability Real World Stats Summary Time to Practice Chapter 6. Creating Graphs: A Picture Really Is Worth a Thousand Words What You Will Learn in This Chapter Why Illustrate Data? Ten Ways to a Great Graphic First Things First: Creating a Frequency Distribution The Plot Thickens: Creating a Histogram The Next Step: A Frequency Polygon Other Cool Ways to Chart Data Using the Computer (R, That Is) to Illustrate Data Real World Stats Summary Time to Practice Chapter 7. Computing Correlation Coefficients: Ice Cream and Crime What You Will Learn in This Chapter What are Correlations All About? Computing a Simple Correlation Coefficient Understanding What the Correlation Coefficient Means A Determined Effort: Squaring the Correlation Coefficient Other Cool Correlations Parting Ways: A Bit About Partial Correlations Summary Time to Practice Chapter 8: Understanding Reliability and Validity: Just the Truth What You Will Learn in This Chapter An Introduction to Reliability and Validity Reliability: Doing it Again Until You Get it Right Different Types of Reliability How Big is Big? Finally: Interpreting Reliability Coefficients Validity: Whoa! What is the Truth? A Last Friendly Word Validity and Reliability: Really Close Cousins Real World Stats Summary Time to Practice Part IV Taking Chances for Fun and Profit Chapter 9. Hypotheticals and You: Testing Your Questions What You Will Learn in This Chapter So You Want to Be a Scientist Samples and Populations The Null Hypothesis The Research Hypothesis What Makes a Good Hypothesis? Real-World Stats Summary Time to Practice Chapter 10. Probability and Why It Counts: Fun with a Bell-Shaped Curve What You'll Learn About in this Chapter W