Abstract
Karl Pearson’s statistical innovations have led to the development of several mathematical statistics techniques. His mathematical contributions to the theory of evolution include a family of univariate probability distributions (referred to as Pearson’s family of distributions), which is found to be useful even today for fitting on data arising from various scientific disciplines (physics, biology, anthropology, economics, etc.). Frequency curve (histogram) for continuous data, a commonly used non-parametric density estimator, owes its origin to him. Pearson’s correlation coefficient is a popular descriptive measure of the linear relationship between two continuous random variables. This article aims to highlight a few of his fundamental ideas.
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Acknowledgement
The author would like to thank Prof. K.S. Mallikarjuna Rao of IIT Bombay and Prof. Debasis Sengupta of ISI Kolkata and the editor for their valuable comments that improved this write-up significantly.
Additional information
Radhendushka Srivastava is a postgraduate (2005) in statistics from the University of Lucknow. He holds a PhD (2006–2011) in statistics from Indian Statistical Institute, Kolkata, and was a post-doctoral associate at Cornell University (2011–2013). He subsequently joined the Department of Mathematics at IIT Bombay (2013—till date).
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Srivastava, R. Karl Pearson and “Applied” Statistics. Reson 28, 183–189 (2023). https://doi.org/10.1007/s12045-023-1542-3
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DOI: https://doi.org/10.1007/s12045-023-1542-3