Successful investing requires the ability to distinguish long-term trends from the short-term noise that moves stock prices on a minute-to-minute basis. One way to tune out the random oscillations and ...

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 ...

Andriy Blokhin has 5+ years of professional experience in public accounting, personal investing, and as a senior auditor with Ernst & Young. Thomas J Catalano is a CFP and Registered Investment ...

Regression models predict outcomes like housing prices from various inputs. Machine learning enhances regression by analyzing large, complex datasets. Different regression types address varied data ...

The purpose of this tutorial is to continue our exploration of regression by constructing linear models with two or more explanatory variables. This is an extension of Lesson 9. I will start with a ...

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 ...

Successful investing requires the ability to distinguish long-term trends from the short-term noise that moves stock prices on a minute-to-minute basis. One way to tune out the random oscillations and ...

Last month we explored how to model a simple relationship between two variables, such as the dependence of weight on height 1. In the more realistic scenario of dependence on several variables, we can ...