Do you have a problem where one variable might affect the other; say the height of the individual can be affected by variables like age, height, and diet? Try simple or multiple linear regression calculators to find the best outcome for your data. The linear regression method is one of the most rewarded methods used in various domains to see meaningful results. From business analytics to machine learning, linear regression has significant importance. Here we are offering you a detailed sight about simple linear regression, its example and uses:

## Defining Simple Linear Regression Calculator:

In statistics, Simple linear regression calculation is used to find the relationship between two continuous variables. Here one variable denotes as X is taken as an explanatory, predictor, or independent variable, which ultimately defines the other variable denoted as Y that is considered as an outcome, response, or dependent variable. To explain x and y variable predictor and the experts commonly use response terms.

Simple linear regression method as the term definition is used for defining only one predictor variable, for example, the relation of height to age. On the other hand, multiple linear regression method is used to describe various predictor variable, for example, the relationship of height to age and diet.

However, simple linear regression can only define the statistical relationship but a not deterministic relationship.

Deterministic relationship: It is the relationship between two variables where predictors can accurately express each other. For example, by calculating kilometres, one can define it in meters.

Statistical relationship: the statistical relationship is incapable of deterring the relationship between two variables like, for example, the involvement of weight gain and calorie intake as weight gain depends on many other factors like your metabolism, rate of exercise, and more.