Bivariate statistical measures regression and correlation

Bivariate statistical measures regression and correlation

1. regression and correlation analysis

   • Regression and correlation analysis includes the analysis of two sample data to find out how two or more variables in a population relate to each other.
     • regression analysis
       • Regression analysis gives rise to a mathematical equation that allows us to describe the relationship between two variables, that is, obtain an "ideal" line known as a regression line.
     • correlation analysis
       • Correlation analysis describes the degree or strength with which this relationship occurs, for this we use a measure known as correlation coefficient or Pearson correlation.

2. bivariate statistics

   • Bivariate statistical techniques allow the joint analysis of two characteristics of individuals in a population with the purpose of detecting possible relationships between them.
     • both quantitative variables
       • questionnaire
       • condensed code table
         • table of frecuency
           • graphic representation
       • data table
     • both quantitative variables
       • Dispersion diagram
       • pearson linear correlation coefficient
         • The percentage of variability of (y) explained by the variability of (x) is measured by the coefficient of determination that corresponds to r2
           • x: score in a learning system y: cost associated with achieving the score
       • inference
         • Ha: the variables are not independent (related variables)
         • Ho: the variables are independent (unrelated variables)

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