BIVARIATE REGRESSION AND CORRELATION STATISTICS

BIVARIATE REGRESSION AND CORRELATION STATISTICS

1. regression analysis

   • It allows us to describe the relationship between two variables. X - Y
     • allows you to predict the value or mean of a variable, named DEPENDENT
       • linear function: (x)=mx+n second degree parabola: y=f(x)=ax2+bx+c function exponential: f (x) = k · ax potential function :f (x) = axn
     • based on a value or average called INDEPENDENT, a value of the dependent variant can be calculated

2. correlation analysis

   • examine the direction and strength of association between two quantitative variables

3. graphically the cloud or point diagram, allows to obtain information about the type of relationship between X and Y

4. linear regression and correlation

   • simple regression
     • consists in generating a regression model that allows explaining the linear relationship that exists between two variables.
   • weighted regression
     • deals with when the assumption of equal variances is not met in the linear regression model

5. parabolic regression

   • Statistical processes for estimating relationships between variables. try to fit a mathematical function to a point cloud that approximates the data

6. regression and multiple correlation

   • working with more than two independent variables, related to each other

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