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Bivariate statistical measures regression and correlation

Maria Camila Romero Melendez English

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Bivariate statistical measures regression and correlation

  1. They allow the joint analysis of two characteristics of the individuals of a population.

    • In order to detect possible relationships between them.
  2. Linear regression

    • It is a method used to forecast or predict the value of one variable as a function of the given values ​​of the other.
      • Simple regression
        • Simple linear regression examines the relationship linear between two continuous variables: a response (Y) and a predictor (X).
      • Multiple regression
        • Multiple linear regression examines the linear relationships between a response continuous and two or more predictors.
  3. Linear correlation

    • Determines the degree of relationship that exists between two variables.
      • Positive correlation
        • It occurs when increasing or decreasing the values ​​of the independent variable increases or those of the dependent variable decrease.
      • Negative correlation
        • Occurs when increasing the values ​​of the independent variable values ​​decrease of the dependent variable or vice versa.
  4. They can be represented graphically on a Cartesian plane

    • Using a scatterplot

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Mind Map on Bivariate statistical measures regression and correlation, created by Maria Camila Romero Melendez on 25/11/2022.
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  • Created by Maria Camila Romero Melendez · May 13, 2021
  • Copied by Maria Camila Romero Melendez · Nov 25, 2022
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