Partial derivatives of a polynomial in one variable. Differentiation of a polynomial and a Cobb-Douglas function of two variables with respect to each variable. Finding the maximum or the minimum of a ...

In this chapter, we introduce the concept of a random variable and develop the procedures for characterizing random variables, including the cumulative distribution function, as well as the ...

In the last section, you learned how to perform a basic linear regression with a single predictor variable. Here, you'll explore how to perform linear regressions using multiple independent variables ...

This article compares the two approaches (linear model on the one hand and two versions of random forests on the other hand) and finds both striking similarities and differences, some of which can be ...

The importance of having improved bounds is illustrated through a non-linear programming problem with stochastic objective function, known as the "wait and see" problem.

Learn how to choose between linear and nonlinear regression models for your data analysis, based on fit, inference, and simplicity criteria.

Linear Regression is like trying to draw the best straight line through a scatter of dots on a graph. It’s a way to predict a value (like someone’s weight) based on another known value (like their ...