Linear regression is used **to quantify the relationship between ≥1 independent (predictor) variables and a continuous dependent (outcome) variable**. … Linear regression is an extremely versatile technique that can be used to address a variety of research questions and study aims.

## Secondly, how do you describe a linear regression line?

The linear regression model describes the dependent variable with a straight line that is defined by **the equation Y = a + b × X**, where a is the y-intersect of the line, and b is its slope. … The regression line enables one to predict the value of the dependent variable Y from that of the independent variable X.

**a quantitative response**whereas a logistic regression is used with a qualitative response (binary results between 0 and 1).

## Also question is, what are the types of linear regression?

Linear Regression is generally classified into two types:

**Simple Linear Regression**. **Multiple Linear Regression**.

## What is linear regression explain with example?

Linear regression **quantifies the relationship between one or more predictor variable(s) and one outcome variable**. … For example, it can be used to quantify the relative impacts of age, gender, and diet (the predictor variables) on height (the outcome variable).

## What is linear regression research paper?

Linear regression **measures the association between two variables**. It is a modeling technique where a dependent variable is predicted based on one or more independent variables. Linear regression analysis is the most widely used of all statistical techniques.

## What is the advantage of using regression analysis?

The importance of regression analysis is that it is all about data: data means numbers and figures that actually define your business. The advantages of regression analysis is that **it can allow you to essentially crunch the numbers to help you make better decisions for your business currently and into the future**.