Visualizing the Regression Lines and the Correlation Coefficient for Bivariate Discrete Random Variables

Sarkar and Rashid (2024) visualized the joint probabilities of two discrete random variables using a 2D disc plot from which they graphically obtained the conditional distributions of Y given X=a, and X given Y= b; and the marginal distributions of X, Y, X+Y, X-Y, and cX+dY. Sarkar and Rashid (2025) visualized the mean, mean deviation, and standard deviation of any discrete random variable using a disc plot. Here, starting with the 2D disc plot, we visualize the correlation coefficient between X and Y, and the linear regression of one variable from the other. Such visualizations help users better comprehend these concepts. Thus, this paper develops a unified geometric framework to visualize conditional means, the overall mean vector, least-squares regression lines, and the correlation coefficient, starting from the disc plot.

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Publication Details

Journal
Journal of Probability and Statistical Science
Published
2026-10-26
DOI
https://doi.org/10.37119/jpss2026.v24i2.1128
Primary Topic
Statistics Education and Methodologies
Type
article
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article

Visualizing the Regression Lines and the Correlation Coefficient for Bivariate Discrete Random Variables

Jyotirmoy Sarkar, Mamunur Rashid
Journal of Probability and Statistical Science
Statistics Education and Methodologies
article

Visualizing the Regression Lines and the Correlation Coefficient for Bivariate Discrete Random Variables

Jyotirmoy Sarkar, Mamunur Rashid
article en

Abstract

Sarkar and Rashid (2024) visualized the joint probabilities of two discrete random variables using a 2D disc plot from which they graphically obtained the conditional distributions of Y given X=a, and X given Y= b; and the marginal distributions of X, Y, X+Y, X-Y, and cX+dY. Sarkar and Rashid (2025) visualized the mean, mean deviation, and standard deviation of any discrete random variable using a disc plot. Here, starting with the 2D disc plot, we visualize the correlation coefficient between X and Y, and the linear regression of one variable from the other. Such visualizations help users better comprehend these concepts. Thus, this paper develops a unified geometric framework to visualize conditional means, the overall mean vector, least-squares regression lines, and the correlation coefficient, starting from the disc plot.

Journal of Probability and Statistical ScienceVol. 24(2)
DePauw University (US), Indiana University Indianapolis (US)
Openalex Percentile: Top 12%
Statistics Education and Methodologies
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