Preface
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I. DESCRIPTIVE STATISTICS
1. Introduction to Statistics
Stumbling Blocks to Statistics
A Brief Look at the History of Statistics
Gertrude Cox (1900-1978)
Benefits of a Course in Statistics
General
Fields of Statistics
Summary
Key Terms and Names
Problems
2. Percentages, Graphs and Measures of Central Tendency
Percentage Changes-Comparing Increases with Decreases
Graphs
Measures of Central Tendency
Appropriate Use of the Mean
the Median and the Mode
Summary
Key Terms
Problems
Computer Problems
3. Variability
Measures of Variability
Graphs and Variability
Questionnaire Percentages
Key Terms
Computer Problems
4. The Normal Curve and z Scores
The Normal Curve
z Scores
Carl Friedrich Gauss (1777-1855)
Translating Raw Scores into z Scores
z Score Translation in Practice
Fun with your Calculator
Summary
Key Terms and Names
Problems
5. z Scores Revisited: T Scores and Other Normal Curve Transformations
Other Applications of the z Score
The Percentile Table
T Scores
Normal Cure Equivalents
Stanines
Grade-Equivalent Scores: A Note of Caution
The Importance of the z Score
Summary
Key Terms
Problems
6. Probability
The Definition of Probability
Blaise Pascal (1623-1662)
Probability and Percentage Areas of the Normal Curve
Combining Probabilities for Independent Events
A Reminder about Logic
Summary
Key Terms
Problems
II. INFERENTIAL STATISTICS
7. Statistics and Parameters
Generalizing from the Few to the Many
Key Concepts of Inferential Statistics
Techniques of Sampling
Sampling Distributions
Infinite versus Finite Sampling
Galton and the Concept of Error
Back to z
Some Words of Encouragement
Summary
Key Terms
Problems
8. Parameter Estimates and Hypothesis Testing
Estimating the Population Standard Deviation
Estimating the Standard Error of the Mean
Estimating the Population of the Mean: Interval Estimates and Hypothesis Testing
The t Ratio
The Type 1 Error
Alpha Levels
Effect Size
Interval Estimates: No Hypothesis Test Needed
Summary
Key Terms
Problems
Computer Problems
9. The Fundamentals of Research Methodology
Research Strategies
Independent and Dependent Variables
The Cause-and-Effect Trap
Theory of Measurement
Research: Experimental versus Post Facto
The Experimental Method: The Case of Cause and Effect
Creating Equivalent Groups: The True Experiment
Designing the True Experiment
The Hawthorne Effect
Repeated-Measures Designs with Separate Control Groups
Requirements for the True Experiment
Post Facto-Research
Combination Research
Research Errors
Experimental Errors
Meta-Analysis
Methodology as a Basis for More Sophisticated Techniques
Summary
Key Terms
Problems
10. The Hypothesis of Difference
Sampling Distribution of Differences
Estimated Standard Error of Difference
Two-Sample t Test for Independent Samples
Significance
William Sealy Gossett (1876-1937)
Two-Tailed t Table
Alpha Levels and Confidence Level
The Minimum Difference
Outliner
One-Tail t Test
Importance of Having at Least Two Samples
Power
Effect Size
Summary
Key Terms
Problems
Computer Problems
11. The Hypothesis of Association: Correlation
Cause and Effect
The Pearson r
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