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Chapter 15

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Strategies When Population Distributions are Not Normal:

Data Transformations and

Rank-Order Tests

- Populations follow a normal curve
- Populations have equal variances
- Ceiling and floor effects

- Data transformation
- Square-root transformation

- Legitimacy of data transformations
- Kinds of data transformations
- Square root transformation
- Log transformation
- Inverse transformation
- Arcsine transformation

- Rank-order transformation
- Rank-order tests
- Nonparametric tests
- Parametric tests

- Basic logic
- The null hypothesis
- Normal curve approximations
- Using parametric tests with rank-transformed data

- Advantages and disadvantages
- Relative risk of Type I and Type II errors

- Computer-intensive methods
- Randomization tests
- Proposed alternative to parametric and nonparametric methods
- Widely applicable
- Unfamiliar to researchers

- Data transformations
- Described just prior to analyses using them

- Rank-order methods
- Described much like any other kind of hypothesis test