Bivariate statistical measures of regression and correlation

Więcej takich

Correlation Method (Farida)

przez farida tarek

Correlation

przez zakareya salem

Logan sci,fair

przez Steve Bloom

correlation

przez Sandra Liliana

Bivariate statistical measures of regression and correlation

Regression

Variable Types

Dependent variables:

are the attributes on which we want to measure changes or make predictions.

Independent variable:

they represent inputs or causes, that is, potential reasons for variation.

The regression allows to calculate a conditional (average) expectation.

Build a function that allows estimating the future value of the study variable.

Regression analysis is a process that analyzes the link between a dependent variable and one or more independent variables.

It is a tool frequently used in statistics, which allows to investigate the relationships between different quantitative dependent variables.

Correlation

degrees of correlation

null correlation:

here there is no type of pattern or relationship between them.

weak correlation:

it will be weak the further apart the points are on the line.

strong correlation:

the correlation will be strong the closer the points are to the line.

Correlation coefficient

It is a measure that allows knowing the degree of linear association between two quantitative variables (X, Y).

Correlation Types

Null correlation:

occurs when there is no dependency of any kind between the variables. In this case it is said that the variables are uncorrelated and the cloud of points has a rounded shape.

Inverse correlation:

occurs when increasing one of the variables, the other decreases. The line corresponding to the cloud of points of the distribution is a decreasing line.

Direct correlation:

occurs when increasing one of the variables, the other increases. The line corresponding to the cloud of points of the distribution is a growing line.