Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Statistics: detecting differences among groups.

Current protocols in protein science - 1 May 2001

Robakiewicz P, Ryder E F

Abstract excerpt

Some of the statistical tests most commonly used (and misused) in biological research are presented here. The tests discussed are those used for comparisons among groups (e.g., t test and ANOVA). The purpose of this appendix is to enable the investigator to determine rapidly the most appropriate...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Bacteria
Share to Densitometry
Share to Immunoprecipitation

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Matched-Pair Analysis

Share to Nephelometry and Turbidimetry

Share to Neurites

Share to Statistics as Topic

Share to Statistics, Nonparametric

Source

Identifiers

PMID: 18429074
DOI: 10.1002/0471140864.psa03gs21

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026. Prepared record publication-18429074-2026-09-02.2. Manifest publication-graph-cohort-2026-09-02.2.

Source receipt: PubMed via Helena Literature Corpus, retrieved 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Statistics: detecting differences among groups.PMID 18429074Read ↗

[Evaluating the significance of differences between variants].Semantic proximity Read ↗

[2 easy statistical methods, involving a minimum of calculations, useful in biology and medicine].Semantic proximity Read ↗

Descriptive statistics of data: understanding the data set and phenotypes of interest.Semantic proximity Read ↗

Ethical principles and guidelines for scientific experiments on animals.Semantic proximity Read ↗

GeneANOVA--gene expression analysis of variance.Semantic proximity Read ↗

A robust procedure for comparing multiple means under heteroscedasticity in unbalanced designs.Semantic proximity Read ↗

Checking the Assumptions of Your Statistical Model Without Getting ParanoidSemantic proximity Read ↗

[Experimental verification of several hypothesis and methods of statistical genetics. 1].Semantic proximity Read ↗

Better tools, new problems: New technologies help to advance research in the life sciences, but the quantities of data generated are proving hard to manage and interpret.Semantic proximity Read ↗

Commentary: the analysis of variance is an analysis of causes (of a very circumscribed kind).Semantic proximity Read ↗

Microarray data analysis: a hierarchical T-test to handle heteroscedasticity.Semantic proximity Read ↗

Using ANOVA to analyze microarray data.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.