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Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 48, No. 3 (1999), pp. 313-329 (17 pages) The number of variables in a regression model is often too large and a more ...

The standard linear regression model does not apply when the effect of one explanatory variable on the dependent variable depends on the value of another explanatory variable. In this case, the ...

Statistical modeling lies at the heart of data science. Well-crafted statistical models allow data scientists to draw conclusions about the world from the limited information present in their data. In ...

In this module, we will introduce the basic conceptual framework for statistical modeling in general, and linear statistical models in particular. In this module, we will learn how to fit linear ...

image: This book offers an introduction to concepts of probability theory, probability distributions relevant in the applied sciences, as well as basics of sampling distributions, estimation and ...

The Annals of Statistics, Vol. 28, No. 5 (Oct., 2000), pp. 1245-1278 (34 pages) The interval mapping method has been shown to be a powerful tool for mapping QTL. However, it is still a challenge to ...

In a data-driven world, the ability to analyze and interpret information is critical. Harvard University’s Professional ...