simple linear regression equation for sample

The linearity of the linear relationship can be determined by calculating the t-test statistic. Why is a t-test used in the linear regression model? An example of multiple linear regression is Y = aX + bZ. Multiple linear regression: Multiple linear regression is defined as linear regression with more than one predictor variable along with its coefficients.An example of a simple linear regression is Y = mX + b. Simple linear regression: Simple linear regression is defined as linear regression with a single predictor variable.Linear regression is of two different types such as the following: The diagram below represents the linear regression line, dependent (response) and independent (predictor) variables. The linear slope, m, can also be termed as the coefficient of the predictor variable. Where Y represents the response variable or dependent variable, X represents the predictor variable or independent variable, m represents the linear slope and b represents the linear intercept. The linear regression line can be represented by the equation such as the following: It can as well be called the statistical linear model.

A linear regression equation can also be called the linear regression model. In other words, it is a statistical technique that is used to determine if there is a linear correlation between the response and predictor variables.

Linear regression is defined as a linear relationship between the response variable and predictor variables.

Why is a t-test used in the linear regression model?.

Simple linear regression equation for sample