Learn how the line of best fit in regression analysis shows relationships between variables, how it's calculated, and its ...

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

This course consists of two sections: Section 1 demonstrates linear regression to model the linear relationship between a response and predictor(s) when both the response and predictors are continuous ...

This article develops a method of calculating iterative estimates of the coefficients of a set of linear regression equations. There are p equations such that the explanatory variables are ...

Martinez-Jerez, Francisco de Asis, and Ariel Andres Blumenkranc. "Using Regression Analysis to Estimate Time Equations." Harvard Business School Background Note 111-001, September 2010. (Revised ...

Abstract. We design a numerical scheme for solving the Multi-step Forward Dynamic Programming (MDP) equation arising from the time-discretization of backward stochastic differential equations. The ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

During the course of operation, businesses accumulate all kinds of data such as numbers related to sales performance and profit, and information about clients. Companies often seek out employees with ...

Capture relationships between data sets by graphing linear equations in Microsoft Excel 2007. Linear equations allow you to predict values within your data set and view the overall trend. Use ...