Parametric Statistical Inference for Comparing Means and Variances.

ABSTRACT:

Purpose

The purpose of this tutorial is to provide visual scientists with various approaches for comparing two or more groups of data using parametric statistical tests, which require that the distribution of data within each group is normal (Gaussian). Non-parametric tests are used for inference when the sample data are not normally distributed or the sample is too small to assess its true distribution.

Methods

Methods are reviewed using retinal thickness, as measured by optical coherence tomography (OCT), as an example for comparing two or more group means. The following parametric statistical approaches are presented for different situations: two-sample t-test, Analysis of Variance (ANOVA), paired t-test, and the analysis of repeated measures data using a linear mixed-eff

SUBMITTER: Ledolter J 

PROVIDER: S-EPMC7425781 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature