Power
The power of a statistical test is the probability that the selected test will appropriately reject the null hypothesis (i.e., when an alternative hypothesis is true). That is, it refers to the likelihood that the test will not make a Type II error (false negative rate or β). Because power is equal to 1–β, as Type II error decreases, power increases. Statistical power is influenced by statistical significance, effect size, and sample size. All of these factors are taken into consideration when completing a power analysis.
Several factors influence power, or the ability to detect significant results if they exist: statistical significance, effect size, and sample size. Each of these terms is described in this section.
The significance level (α) is the ...
Looks like you do not have access to this content.
Reader's Guide
Descriptive Statistics
Distributions
Graphical Displays of Data
Hypothesis Testing
Important Publications
Inferential Statistics
Item Response Theory
Mathematical Concepts
Measurement Concepts
Organizations
Publishing
Qualitative Research
Reliability of Scores
Research Design Concepts
Research Designs
Research Ethics
Research Process
Research Validity Issues
Sampling
Scaling
Software Applications
Statistical Assumptions
Statistical Concepts
Statistical Procedures
Statistical Tests
Theories, Laws, and Principles
Types of Variables
Validity of Scores
- 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
Research Methods
