Goodness-of-Fit Tests
Goodness-of-fit tests include various tests that measure how well a statistical model (which is built from theory) fits the observed data. Depending on the types of distributions and the nature of the variables being examined, different goodness-of-fit tests are used. Commonly used tests include Pearson’s chi-square (χ2) test and R2 measure of goodness of fit. This entry describes the rationale of each test and the steps taken to conduct each test.
Pearson’s χ2 test is a goodness-of-fit test used in the context of discrete distributions (i.e., the data are categorical in nature). Introduced by Karl Pearson in 1900, Pearson’s χ2 test evaluates whether the frequency of observations in each category statistically differs from the theoretical prediction. A “good fit” model indicates we can reasonably ...
Looks like you do not have access to this content.
Reader's Guide
Assessment
Cognitive and Affective Variables
Data Visualization Methods
Disabilities and Disorders
Distributions
Educational Policies
Evaluation Concepts
Evaluation Designs
Human Development
Instrument Development
Organizations and Government Agencies
Professional Issues
Publishing
Qualitative Research
Research Concepts
Research Designs
Research Methods
Research Tools
Social and Ethical Issues
Social Network Analysis
Statistics
Teaching and Learning
Theories and Conceptual Frameworks
Threats to Research Validity
- All
- A
- B
- C
- D
- E
- F
- G
- H
- I
- J
- K
- L
- M
- N
- O
- P
- Q
- R
- S
- T
- U
- V
- W
- X
- Y
- Z