bivariate statistical measures

bivariate statistical measures

1. Determination coefficient R2

   • simple linear correlation
     • positive correlation and negative correlation
       • - Dispersion diagram
         • - regression
           • simple regression

2. regression analysis

   • studies the relationship between two quantitative variables
     • studies the strength of the association through a measure of association called the correlation coefficient

3. regression problems

   • inhomogeneous variance
     • nonlinear relationship
       • correlated errors

4. linear regression

   • Pearson's linear correlation coefficient
     • R is useful to determine if there is a linear relationship between two variables, but it will not work for (quadratics, logarithmic)

5. simple regression model

   • if the y^ since they rarely coincide no matter how good the regression model is, the quantity " -e Y-y^" is called the residual error

6. correlation

   • analysis of two quantitative variables
     • the coordinates on the Cartesian axes are the values that the two values take for the observation
       • taking into account the dependent and independent variables
   • mutual relationship, measures and indicates the degree and values of a variable when related to another variable
     • the correlation does not distinguish between, response variable
       • positive linear correlation
         • has a median value, because not all the points are included in the line, null: not all are associated, positive linear, strong: all the values are on the line, strong negative linear