Reading a research article part II: parametric and nonparametric statistics
- Resource Type
- Authors
- Dana Oliver; Suzanne M. Mahon
- Source
- Scopus-Elsevier
- Subject
- media_common.quotation_subject
Normal Distribution
Breast Neoplasms
Data type
Statistics, Nonparametric
Treatment and control groups
Random Allocation
Age Distribution
Medicine
Humans
Semiparametric regression
Selection Bias
General Environmental Science
media_common
Parametric statistics
Proportional Hazards Models
Selection bias
Analysis of Variance
Chi-Square Distribution
business.industry
Nonparametric statistics
Reproducibility of Results
Pattern recognition
Confounding Factors, Epidemiologic
Data science
Survival Analysis
Semiparametric model
Variable (computer science)
Nursing Research
Research Design
Data Interpretation, Statistical
Sample Size
General Earth and Planetary Sciences
Female
Artificial intelligence
business
Algorithms
- Language
Researchers often try to use a randomization technique in an attempt to reduce bias and ensure that treatment and control groups are as similar as possible. This article has provided an overview of how researchers might use parametric and nonparametric statistics when analyzing data and looking for differences between groups. Researchers must consider the types of data and choose the tests that are appropriate for the variable types to draw appropriate conclusions. The next article in this series will address comparison of more than two groups and repeated measures and other design issues.