## Linear Regression

A way to model the relationship of a one or more explanatory variables to a dependent variable

### Types Of Linear Regression

• Simple Linear Regression - One explanatory variable
• Multiple Linear Regression - More than one explanatory variable

### Simple Linear Regression

y = beta_0 + beta_1 x

• y - response variable
• x - explanatory variable
• B0 - intercept
• B1 - slope

### Pearson’s Correlation

Correlation is a linear association between two scalar variables

R or Pearson’s R - Correlation coefficient

• always between -1 and 1
• no unit
• corr(x, y) = corr(y, x)
• magnitude indicates strength
e_i = y_i - hat y_i