Measures of Variability
Observations within a data set are not of equal value; they vary along a given scale. The extent to which they vary between and among themselves can be indicated by measures of variation or variability. Measures of variability show the amount of dispersion in the data set or, in other words, how much the observations or values are spread out along the scale. Dispersion within a data set can be measured or described in several ways, including the range, interquartile range, and standard deviation. This entry provides a definition, description, and calculation of each measure of variability along with advantages and disadvantages in using each. It also includes a discussion of standard deviation in a normal distribution, or the empirical rule, and Chebyshev’s theorem.
Measures of ...
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