Data Analysis Using Python > Regression > Types of Regression

Types of Regression

1. Simple linear regression uses one independent variable to explain or predict the outcome of the dependent variable Y.

              Score = 40.5 + 7.2 * hours + e

              Y=a+bX+e

2. Multiple linear regression uses two or more independent variables to predict the outcome.

         Score = 40.5 + 7.2 * hours + 5.1 * Age + e

         Y=a+b₁​X₁​+b₂​X₂ ​+e

And using generalization

      Y=a+b₁​X₁​+b₂​X₂​+b₃​X₃​+...+b_t​Xt​+_e

where:

Y=The dependent variable you are trying to predictor explain

X=The explanatory (independent) variable(s) you are using to predict or associate with Y

a=The yintercept

b=(beta coefficient) is the slope of the explanatoryvariable(s)

e=The regression residual or error term​

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Assumptions of Simple Linear Regression

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