Interpreting Correlations

An Interactive Visualization

Created by Kristoffer Magnusson

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Correlation is one of the most widely used tools in statistics. The correlation coefficient summarizes the association between two variables. In this visualization I show a scatter plot of two variables with a given correlation. The variables are samples from the standard normal distribution, which are then transformed to have a given correlation by using Cholesky decomposition. By moving the slider you will see how the shape of the data changes as the association becomes stronger or weaker. You can also look at the Venn diagram to see the amount of shared variance between the variables. It is also possible drag the data points to see how the correlation is influenced by outliers.

Correlation

Correlation: 0.00

Shared variance: 0%

y = 100.00 + 0.00*x

Mean(y) = 100.00

Mean(x) = 100.00

SD(y) = 3.00

SD(x) = 5.00

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Written by Kristoffer Magnusson, a researcher in clinical psychology. You should follow him on Twitter and come hang out on the open science discord Git Gud Science.

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APA 7

Magnusson, K. (2020). Interpreting Correlations: An interactive visualization (Version 0.6.4) [Web App]. R Psychologist. https://rpsychologist.com/correlation/

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Please report errors or suggestions by opening an issue on GitHub, if you want to ask a question use GitHub discussions

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Yes, go ahead! I did not invent plotting two overlapping Gaussian distributions. This visualization is dedicated to the public domain, which means “you can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission” (see Creative common’s CC0-license). Although, attribution is not required it is always appreciated!

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I've been looking for applets that show this for YEARS, for demonstrations for classes. Thank you so much! Students do not need to tolarate my whiteboard scrawl now. I'm sure they'd appreciate you, too.l

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Wonderful work!

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Thank you for sharing your visualization skills with the rest of us! I use them frequently when teaching intro stats. 

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Webmentions

Juan Ramón
Juan Ramón 2021-03-23
Esto es una correlación de 0.30. A puro ojo no es tan fácil saber si la línea habría de ser creciente, decreciente o con pendiente nula. El porcentaje de varianza explicada es de solo el 9%. (Tomado de aquí). rpsychologist.com/correlation/
Jamie Lingwood
Jamie Lingwood 2021-03-05
I've been using this fantastic interactive resource from @krstoffr to help my first year students visualise what different Correlations look like. Particularly handy for explaining tricky concepts such as shared variance: rpsychologist.com/correlation/
Thùy Vy T Nguyễn, PhD ☕️💻📄
I was in a talk by @MalvikaSharan; she mentioned #OpenScience jargons can make you feel you can't keep up. To me, jargons is challenging b/c I learn better w images I really appreciate those who create tools to break down complicated concepts like this rpsychologist.com/correlation/
Dr. #ResearchLiteracy 📊📈
Just found this great data visualization teaching tool created by @krstoffr. Will be using the one on #correlation in my graduate research methods course this week. #ResearchLiteracy @AcademicChatter @OpenAcademics rpsychologist.com/correlation/

(Webmentions sent before 2021 will unfortunately not show up here.)

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