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Bivariate statistical measures regression and correlation
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Bivariate statistical measures regression and correlation
They allow the joint analysis of two characteristics of the individuals of a population.
- In order to detect possible relationships between them.
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.
- Simple 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.
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.
- Positive correlation
- Determines the degree of relationship that exists between two variables.
They can be represented graphically on a Cartesian plane
- Using a scatterplot
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- Mindmap am Bivariate statistical measures regression and correlation, erstellt von Maria Camila Romero Melendez am 25/11/2022.
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- Maria Camila Romero Melendez
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- Erstellt von Maria Camila Romero Melendez · 13 Mai 2021
- Kopiert von Maria Camila Romero Melendez · 25 Nov 2022
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