Bivariate statistical measures of regression and correlation-Mayerly Diaz

Problems with regression

Inhomogeneous variance.

non linear relationship

Correlational errors

Bivariate statistical measures

Regression and correlation

Dispersion diagram

Correlation

Simple Linear Regression

Multiple Regression

Regression analysis model

Statistical: Allows the incorporation of a random component in the relationship.

Standardized: The slope β1 tells us if there is a relationship between two variables.

Deterministic: That under ideal conditions, the independent variable can be a mathematical function of the independent variables.

Regression analysis

Study the relationship between two quantitative variables

Statistical technique used to derive an equation that relates a criterion variable to one or more predictor variables.

It studies the strength of the association through a measure of association called the correlation coefficient.

Multiple Regression

The regression can be linear and curvilinear or nonlinear, they can be

Regression Coefficient

The regression coefficient can be: Positive, Negative and Null

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.

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.