Bivariate statistical measures regression and correlation

Bivariate statistical measures regression and correlation

1. REGRESSIÓN

   • regression: Relationship between two or more continuous variables
   • Regression line: Describes the relationship or dependency between two or more variables
     • In the case of a single independent variable it can be expressed::
   • The correlation analysis: It describes the degree or strength with which the relationship is produced.
   • A measure known as the correlation coefficient or Pearson correlation is used.
   • The relationship between two variables is classified:
     • One-sided causal dependence: This relationship occurs when one of the variables influences the other, but not vice versa
     • Interdependence: It occurs when the influence between two variables is reciprocal. It would be bilateral dependency.
     • Indirect dependency: it is when two variables can show a correlation through a third variable that influences them.
     • Concordance: It is presented in two independent variables to which the correlation that may exist is determined.
     • Chance covariation: it is when the correlation between the two variables is completely random or accidental.
   • The regression analysis: It allows the prediction, that is, the estimation of a value or average of a variable called dependent.
   • The relationship between two cause and effect variables tells us if the relationship is
     • Parabolic
     • Exponential
     • linear
     • mathematical
   • For each variable it will be possible to calculate the arithmetic measures, the variances and their deviations.
     • we will have a new measure of dispersion called covariance
     • scatterplot or point cloud
       • It allows obtaining information about the type of relationship between x and y.

2. CORRELATION

   • It is the direction and strength of the association between two quantitative variables.
   • Correlation or Pearson coefficient
     • They are not independent, but related.
     • Quantitative variables
   • correlation types
     • Direct correlation: occurs when increasing one of the variables the other increases.
       • corresponding to the cloud of points of the distribution is a growing line.
     • Inverse correlation: occurs when increasing one of the variables the other decreases.
       • The line corresponding to the cloud of points of the distribution is a line decreasing.
     • null correlation: occurs when there is no dependency of any kind between the variables. In this case it is said that the variables are uncorrelated and the cloud of points it has a rounded shape.

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

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