Catégories : Tous - variables - correlation - regression - coefficient

par Mayerly johana Diaz Ariza Il y a 2 années

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Bivariate statistical measures of regression and correlation-Mayerly Diaz

The document delves into the intricacies of bivariate statistical measures, focusing primarily on regression and correlation. It explains the concept of the coefficient of determination, also known as R squared, which assesses how well a model fits a given set of variables.

Bivariate statistical measures of regression and correlation-Mayerly Diaz

Bivariate statistical measures of regression and correlation-Mayerly Diaz

Coefficient of determination R2
Determining the degree of correlation between the variables the coefficient of determination, also called R squared, reflects the goodness of fit of a model to the variable.
The regression can be linear and curvilinear or nonlinear, they can be
Regression Coefficient

Indicates the number of units in which the dependent variable "Y" is modified by the effect of the change in the independent variable "X" or vice versa in a unit of measure.

The regression coefficient can be: Positive, Negative and Null

Regression analysis

It studies the strength of the association through a measure of association called the correlation coefficient.
Statistical technique used to derive an equation that relates a criterion variable to one or more predictor variables.
Study the relationship between two quantitative variables

Regression analysis model

Deterministic: That under ideal conditions, the independent variable can be a mathematical function of the independent variables.
Standardized: The slope β1 tells us if there is a relationship between two variables.
Statistical: Allows the incorporation of a random component in the relationship.

Bivariate statistical measures

Multiple Regression
Simple Linear Regression
Correlation
Dispersion diagram
Regression and correlation

Problems with regression

Correlational errors
non linear relationship
Inhomogeneous variance.