A quantitative study is made of the bias in the usual estimate of the linear correlation coefficient and of the relative efficiency of the estimated regression, when a certain type of selective ...

An international team of mathematicians, led by Lehigh University statistician Taeho Kim, has introduced an innovative method ...

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

Offers an alternative to Markowitz’s “Portfolio Selection”. Outlines the nuts and bolts of correlation between past and future performance, or between expected and actual returns. Explains optimal ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Businesspeople need to demand more from machine learning so they can connect data scientists’ work to relevant action. This requires basic machine learning literacy — what kinds of problems can ...

Correlations and multiple linear regressions were used to develop models relating well water chemical quality parameters to a set of independent chemical variables in post- and pre-monsoon seasons in ...