Bivariate Statistical Measures

Bivariate Statistical Measures

1. Studies the relationship between two or more variables

2. Regression

   • Linear regression
     • used to model the relationship between two variables
       • his calculator is built for simple linear regression
         • where only one predictor variable (X) and one response (Y) are used.
     • estimate the value of a response by using a line-of-best-fit
   • Multiple Linear regression
     • • Multiple Linear Regression is used to estimate the relationship between two or more independent variables and one dependent variable.
     • Multiple Linear Regression (MLR), also known simply as multiple regression, is the most common form linear regression analysis
       • It is a statistical technique that uses several independent variables to predict the outcome of a dependent variable

3. Measure Correlation

   • Correlation is used to test relationships between quantitative variables or categorical variables
     • A correlation coefficient is a way to put a value to the relationship
       • Pearson's measures the strength of the linear relationship between two variables
   • The tendency for two values or variables to change together, in either the same or opposite way
   • Methods

4. Scatter plot

   • It is the most used to graphically analyze bivariate data, that is, two sets of this

Images and files in the map