Bivariate statistical measures

Bivariate statistical measures

1. Regression

   • Statistical process for estimating relationships between variables.
     • Simple linear
       • Allows you to model a relationship between two sets of variables.
         • It is characterized by predicting the dependent variable.
     • Multiple linear
       • It is responsible for analysing situations involving more than one variable.
         • It allows to identify which are the independent variables are those that can explain an independent variable, check the causes and predict approximate values
     • Non-linear
       • More complicated process where it may happen that the number of parameters does not match the number of explanatory variables.

2. Correlation

   • Determines the degree of relationship between two variables
     • Strong correlation: The closer the points on the line are.
     • Weak correlation: When the points of the line are further away.
     • Null correlation: There is no relationship.
     • Correlation coefficients are numbers that vary between positive +1 and negative -1

3. ¿What is it?

   • Allow the joint analysis of two characteristics of individuals in a population in order to detect possible relationships between them.

4. Dispersion diagram

   • A diagram type that uses cartesian coordinates to display the values of two variables for a dataset.

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