Preface

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

Inte