---
title: "Statistics"
chunk: 8/8
source: "https://en.wikipedia.org/wiki/Statistics"
category: "reference"
tags: "science, encyclopedia"
date_saved: "2026-05-05T03:56:59.364659+00:00"
instance: "kb-cron"
---

Who says so? (Do they have an axe to grind?)
How do they know? (Do they have the resources to know the facts?)
What's missing? (Do they give us a complete picture?)
Did someone change the subject? (Do they offer us the right answer to the wrong problem?)
Does it make sense? (Is their conclusion logical and consistent with what we already know?)

=== Misinterpretation: correlation ===

The concept of correlation is particularly noteworthy for the potential confusion it can cause. Statistical analysis of a data set often reveals that two variables (properties) of the population under consideration tend to vary together, as if they were connected. For example, a study of annual income that also looks at age of death, might find that poor people tend to have shorter lives than affluent people. The two variables are said to be correlated; however, they may or may not be the cause of one another. The correlation phenomena could be caused by a third, previously unconsidered phenomenon, called a lurking variable or confounding variable. For this reason, there is no way to immediately infer the existence of a causal relationship between the two variables.

== See also ==

Foundations and major areas of statistics

== References ==

== Further reading ==
Lydia Denworth, "A Significant Problem: Standard scientific methods are under fire. Will anything change?", Scientific American, vol. 321, no. 4 (October 2019), pp. 62–67. "The use of p values for nearly a century [since 1925] to determine statistical significance of experimental results has contributed to an illusion of certainty and [to] reproducibility crises in many scientific fields. There is growing determination to reform statistical analysis... Some [researchers] suggest changing statistical methods, whereas others would do away with a threshold for defining "significant" results". (p. 63.)
Barbara Illowsky; Susan Dean (2014). Introductory Statistics. OpenStax CNX. ISBN 978-1938168208.
Stockburger, David W. "Introductory Statistics: Concepts, Models, and Applications". Missouri State University (3rd Web ed.). Archived from the original on 28 May 2020.
OpenIntro Statistics Archived 16 June 2019 at the Wayback Machine, 3rd edition by Diez, Barr, and Cetinkaya-Rundel
Stephen Jones, 2010. Statistics in Psychology: Explanations without Equations. Palgrave Macmillan. ISBN 978-1137282392.
Cohen, J (1990). "Things I have learned (so far)" (PDF). American Psychologist. 45 (12): 1304–1312. doi:10.1037/0003-066x.45.12.1304. S2CID 7180431. Archived from the original (PDF) on 18 October 2017.
Gigerenzer, G (2004). "Mindless statistics". Journal of Socio-Economics. 33 (5): 587–606. doi:10.1016/j.socec.2004.09.033. hdl:11858/00-001M-0000-0025-87C0-8.
Ioannidis, J.P.A. (2005). "Why most published research findings are false". PLOS Medicine. 2 (4): 696–701. doi:10.1371/journal.pmed.0040168. PMC 1855693. PMID 17456002.

== External links ==

(Electronic Version): TIBCO Software Inc. (2020). Data Science Textbook.
Online Statistics Education: An Interactive Multimedia Course of Study. Developed by Rice University (Lead Developer), University of Houston Clear Lake, Tufts University, and National Science Foundation.
UCLA Statistical Computing Resources (archived 17 July 2006)
Philosophy of Statistics from the Stanford Encyclopedia of Philosophy