Full Description
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. The dataset contains simulated data to represent a random elementary school in the US. This fictitious elementary school consists of grade K-5 and has traditional classes taught in English as well as Spanish immersion classes. The simulated data represents a set of 70 teachers in this school. The dataset allows students to run various practice exercises in SPSS.
Contents
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
