## Methods Toward a Science of Behavior and Experience 10th Edition by William J. Ray – Test Bank

Chapter 7 – Testing the Hypothesis: A Conceptual Introduction

Chapter Outline

The Context of Experimentation: An Example

Types of Variation

Chance Variation

Systematic Variation Due to the Independent Variable

Systematic Variation Due to Confounds

Statistical Hypothesis Testing

Threats to Internal Validity

History

Maturation

Testing

Instrumentation

Statistical Regression

Selection

Mortality

Selection–Maturation Interaction

Diffusion or Imitation of Treatments

Conclusion

Chapter Overview

Interpreting the outcome of an experiment requires making decisions about the source of any variance. These sources may include chance variance, systematic variation due to the independent variable, and systematic variation due to confounds. Each source of variance has implications for the probability of making Type I and Type II errors. Variance is analyzed using the F ratio, which uses within-groups variance (chance or error variance) and between-groups variance.

There are several threats to internal validity. They include history, maturation, testing, instrumentation, statistical regression, selection, mortality, selection-maturation interaction, and diffusion.

Chapter Objectives

1. Evaluation of a research hypothesis is a complex process. Identify three important questions you should consider in your evaluation.

2. What three resources do we use when looking for unknown factors that may be responsible for the experimental outcome?

3. Why is chance always involved in our sampling and observations of the world?

4. Why do we never state that the independent variable absolutely caused the effect on the dependent variable?

5. Why is it essential that the initial phase of any experiment be a statistical decision process?

6. What is the role of confounds in the research process?

7. Why do we try to eliminate sources of uncontrolled variance that operate in a systematic manner?

8. Why do scientists argue that the heart of experimentation lies in ruling out alternative explanations?

9. What is the F-ratio? How can it be explained in terms of within-groups variance and between-groups variance? How does this relate to the treatment effect and error variance?

10. What is the relationship between a calculated F-value that is close to 1 and the null hypothesis? What is the general rule regarding the value of the F-ratio and the certainty of differences between groups that are not caused by chance alone?

## Reviews

There are no reviews yet.