Related Experiment Video
Updated: Nov 26, 2025

Basics of Multivariate Analysis in Neuroimaging Data
Published on: July 24, 2010
Multivariate statistics in the analytical laboratory (1): an introduction
Abstract:
Modern analytical techniques can harvest large amounts of multi-analyte data from multiple sample materials in extremely short periods. Such methods offer much more than major gains in efficiency, cost and time. They can yield information not otherwise available - classification, discrimination, cluster analysis and pattern recognition. Multivariate regression methods are also widely used. All these applications are available in software packages and are readily implemented. The calculations use matrix algebra, but here we outline the basic principles that underpin some of the methods, and show the types of information available.
Related Concept Videos
Introduction to Statistics
In statistics, the collection of individuals or objects under study is called population. The idea of sampling is to select a portion of the larger population...
Statistical Methods to Analyze Parametric Data: ANOVA
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
Overview of Minitab
Introduction to Nonparametric Statistics
One of...
Biostatistics: Overview
Discrete variables are...
Statistical Analysis: Overview
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...

