What is Linear Regression?
Linear Regression is a statistical method used to model the relationship between a dependent variable (also known as the response variable) and one or more independent variables (also known as predictor variables). The goal of Linear Regression is to find the best-fitting line through a set of data points, which can then be used to make predictions about the response variable for different values of the predictor variables.
Linear Regression models are represented by the equation y = mx + b, where y is the response variable, x is the predictor variable, m is the slope of the line, and b is the y-intercept. Simple Linear Regression is used to model the relationship between one predictor variable and one response variable.
Linear Regression is a widely used statistical technique and is often used in fields such as economics, engineering, and the natural sciences.
How to Calculate Simple Linear Regression Line?
Simple Linear Regression Line calculator uses Dependent Random Variable Y = Regression Constant+(Regression Coefficient*Independent Random Variable X) to calculate the Dependent Random Variable Y, Simple Linear Regression Line formula is defined as the value of the dependent random variable Y corresponds to the given value of the independent random variable X determined using the simple linear regression line. Dependent Random Variable Y is denoted by Y symbol.
How to calculate Simple Linear Regression Line using this online calculator? To use this online calculator for Simple Linear Regression Line, enter Regression Constant (b0), Regression Coefficient (b1) & Independent Random Variable X (X) and hit the calculate button. Here is how the Simple Linear Regression Line calculation can be explained with given input values -> 90 = 50+(5*10).