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Bivariate Statistical Measures

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Bivariate Statistical Measures
The relationship between two variables can be classified as:
- dependence hint
- when two variables can show a correlation, through from a third variable that influences in them
- interdependence
- when the influence in the two variables is reciprocal
- would be a case of dependence bilateral
- when the influence in the two variables is reciprocal
- dependence one-sided causation
- when one of the variables influences the other, but not contrary
- agreement
- is presented in two variables independent to which are determines the correlation that It can exist
- covariate casual
- when the correlation that occurs between the two variables is totally causal or accidental
- dependence hint
regression analysis
- math equation that allows to describe the existing relationship between two variables
- help get a regression line
- through:
- through:
- help get a regression line
- allows to measure the force of association between two variables
- in addition, it allows see if the relationship it is linear, parabolic or exponential, among other.
- equation linear
- location of the line in some point
- pending the straight
- math equation that allows to describe the existing relationship between two variables
correlation analysis
- allows the prediction of A variable named earring
- describe the degree or strength with That produces bliss relationship
- measure known as: Correlation coefficient or Pearson correlation
- R = r
- this degree of correlation is obtained by calculating of the correlation coefficient
- measure of interdependence of two random variables
- measure of interdependence of two random variables
- this degree of correlation is obtained by calculating of the correlation coefficient
- coefficient of correlation of Pearson between "y" and "x"
- R = r
- measure known as: Correlation coefficient or Pearson correlation
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- Mind Map on Bivariate Statistical Measures, created by Yeishell Benavides on 16/11/2022.
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- Yeishell Benavides
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