Bivariate statistical measures regression and correlation

Bivariate statistical measures regression and correlation

1. bivariate statistical measures

   • Bivariate statistical techniques allow the joint analysis of two characteristics of the individuals in a population in order to detect possible relationships between them.
   • Bivariate data come from observation simultaneous analysis of two variables (X, Y ) in a sample of n individuals. The data will be pairs of values, numeric or non-numeric, of the form
   • They will be used to describe the two variables jointly or a variable depending on the other
   • Bivariate statistical measures
     • Regression and correlation
     • Dispersion diagram
     • Correlation
     • simple linear regression
     • multiple regression

2. regression analysis

   • studies the relationship between two qualitative variables
   • statistical technique used to derive an equation that relates a criterion variable to one or more predictor variables
   • regression types
     • Variables independientes
     • Dependent variables
       • are those that we seek to study through statistical regression to understand how it adapts by modifying the independent variables
     • .Simple linear regression model
       • Simple linear regression analysis is the most widely used and the simplest of all. It is about studying the effect of an independent variable on a single variable dependent on the first —or that at least at a theoretical level we have considered to be dependent—. Using this simple linear regression equation, an estimate can be made based on the data obtained.
     • Multiple linear regression model
       • In the case of multiple linear regression, we find ourselves with a model that simply has more than one independent variable. We will apply this model when we have reason to believe that there is more than one factor that affects the study variable
     • Nonlinear regression model
       • There are occasions in which the relationship that can occur between independent variables and the dependent variable does not have a linear development, but instead has, for example, an exponential growth. In those cases, the nonlinear regression model comes into play and allows us to approximate the values of the dependent variable in a nonlinear environment
     • Independent variables are the factors that we consider to influence and directly affect the dependent variables that are under study
   • The regression analysis is a statistical process that allows us to analyze the relationship that exists between two or more variables, one of them being dependent on the rest of the variables that we are using in our mathematical calculation

3. correlation

   • correlation methods
     • Regresión Lineal.
     • Nonlinear Regression
     • Logistic regression
     • Probit models
     • Logarithmic models
     • Crosstabs
   • Correlation is a type of association between two numerical variables, specifically evaluating the trend (increasing or decreasing) in the data. Two variables are associated when one variable gives us information about the other

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