About regression analysis

This is an article about regression analysis.

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Today we will learn about regression analysis.

Regression analysis is a statistical method that analyzes the relationship between a dependent variable and one or more independent variables. It is used to identify correlations between data and build predictive models.

Below is information on regression analysis.

Dependent and independent variables

Dependent Variable

A variable that is influenced by other variables and is a variable that is intended to be predicted or explained.

Independent Variable

A variable that affects the dependent variable and explains changes in the dependent variable.

Types of regression analysis

Simple Linear Regression

It is a method of analyzing the relationship between one independent variable and one dependent variable.

Multiple Linear Regression

It is a method of analyzing the relationship between two or more independent variables and one dependent variable.

Logistic Regression

This method is used for classification problems by analyzing the relationship between a binary dependent variable and an independent variable.

Use of regression analysis

prediction

It is used to predict future values ​​based on past data.

Causal analysis

It is used to determine causal relationships between independent and dependent variables.

Variable importance assessment

It is used to evaluate the impact of each independent variable on the dependent variable.

Evaluation of regression analysis

Residual Analysis

Assess the suitability of a model by analyzing the differences between the model’s predicted values ​​and actual values.

Coefficient of determination (R-squared)

It is an indicator of how much the model explains the total variance in the dependent variable.

Conclusion

Regression analysis is an important data analysis technique and is actively used to understand relationships between variables and build predictive models.

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