Should Language Researchers Test for Normality? An Investigation Using Monte Carlo Simulation

This project highlights the problems associated with normality testing in the language sciences. Using two Monte Carlo simulations, these analyses show how normality testing can mislead researchers about the nature of their data and models.

Authors

Publication Details

Journal
OSF Preprints (OSF Preprints)
Published
2026-10-26
DOI
https://doi.org/10.13140/rg.2.2.25992.38404
Primary Topic
Statistical Distribution Estimation and Applications
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Should Language Researchers Test for Normality? An Investigation Using Monte Carlo Simulation

Shawn Hemelstrand
2 links
OSF Preprints (OSF Preprints)
Statistical Distribution Estimation and Applications
preprint

Should Language Researchers Test for Normality? An Investigation Using Monte Carlo Simulation

Shawn Hemelstrand
preprint en

Abstract

This project highlights the problems associated with normality testing in the language sciences. Using two Monte Carlo simulations, these analyses show how normality testing can mislead researchers about the nature of their data and models.

OSF Preprints (OSF Preprints)
Statistical Distribution Estimation and Applications
DOISourceOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon
Should Language Researchers Test for Normality? An Investigation Using Monte Carlo Simulation — Shawn Hemelstrand · OSF Preprints (OSF Preprints) (2026) | TGRS Research Map | TGRS