BIVARIATE STATISTICAL MEASURES

BIVARIATE STATISTICAL MEASURES

1. STATISTICAL MEASURE BIVARIATE REGRESSION

   • Is a statistical technique wich allows us the change in one of the variables calls answer and corresponds to another known colo explanatory variable
     • TYPES
       • SIMPLE LINEAR REGRESSION
         • The relationship is explained that exists between the variable response (Y) and a single explanatory variable (X).
       • MULTIPLE REGRESSION
         • Consists of working with a variable a interval level or ratio. in this way it is achieved analize the relationship between two or more variables through equations.
       • LOGISTIC REGRESSION
         • Used to predict the outcome of a categorical variable (variable you can adopt a limited number of categories) in function of the independent or predictor variables.

2. STATISTICAL MEASURE BIVARIATE CORRELATION

   • This consists of examining the direction and strength of the association between two quantitative variables. the intensity is also known of the relationship between then.
     • TYPES
       • NEGATIVE CORRELATION
         • Consists when the two variables are correlated in reverse.
       • POSITIVE CORRELATION
         • A positive correlation emerges when the two variables are directly correlated.
       • UNCORRELATED
         • Is when you can not make no sense of coevariation.
       • CORRELATION COEFFICIENT
         • Measure of linear dependence between two quantitative random variables.