The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate ...

I 'm a big fan of Python for data analysis, but even I get curious about what else is available. R has long been the go-to language for statistics, but the "Tidyverse" has given the language a serious ...

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 ...

A behind-the-scenes blog about research methods at Pew Research Center. For our latest findings, visit pewresearch.org. Many of Pew Research Center’s survey analyses show relationships between two ...

Beside the model, the other input into a regression analysis is some relevant sample data, consisting of the observed values of the dependent and explanatory variables for a sample of members of the ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

STRI copy 39088014660302 purchased with funds from the S. Dillon Ripley Endowment. SERC copy 39088016914160 purchased with funds from the S. Dillon Ripley Endowment ...

A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the price of a house based on its square footage, age, number of bedrooms and ...