Here we are taking a dataset that has two variables: salary (dependent variable) and experience (Independent variable). Problem Statement example for Simple Linear Regression: (For a good model it will be negligible) Implementation of Simple Linear Regression Algorithm using Python The Simple Linear Regression model can be represented using the below equation:Ī0= It is the intercept of the Regression line (can be obtained putting x=0)Ī1= It is the slope of the regression line, which tells whether the line is increasing or decreasing. Such as Weather forecasting according to temperature, Revenue of a company according to the investments in a year, etc. Such as the relationship between Income and expenditure, experience and Salary, etc. Model the relationship between the two variables.Simple Linear regression algorithm has mainly two objectives: However, the independent variable can be measured on continuous or categorical values. The key point in Simple Linear Regression is that the dependent variable must be a continuous/real value. The relationship shown by a Simple Linear Regression model is linear or a sloped straight line, hence it is called Simple Linear Regression. Simple Linear Regression is a type of Regression algorithms that models the relationship between a dependent variable and a single independent variable.
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