Seifudin beyan Mena
Mar 24
What is different between correlation and regression ?
What is different between correlation and regression ?
1 view
1 view
1 answer
Sort By
ChatGPT
Mar 24
Correlation and regression are both statistical techniques used to measure the relationship between two variables, but they have some key differences:
1. Purpose: Correlation is used to measure the strength and direction of a linear relationship between two variables, while regression is used to predict the value of one variable based on the value of another variable.
2. Direction: Correlation measures the strength and direction of the relationship between two variables, but does not imply causation. Regression, on the other hand, can be used to determine the causal relationship between variables.
3. Output: Correlation produces a correlation coefficient, which ranges from -1 to 1, indicating the strength and direction of the relationship. Regression produces an equation that can be used to predict the value of one variable based on the value of another variable.
4. Use of variables: In correlation, both variables are treated as independent and equal, while in regression, one variable is considered the independent variable (predictor) and the other is considered the dependent variable (outcome).
5. Interpretation: Correlation is used to determine if there is a relationship between two variables, while regression is used to quantify the relationship and make predictions based on that relationship.
1. Purpose: Correlation is used to measure the strength and direction of a linear relationship between two variables, while regression is used to predict the value of one variable based on the value of another variable.
2. Direction: Correlation measures the strength and direction of the relationship between two variables, but does not imply causation. Regression, on the other hand, can be used to determine the causal relationship between variables.
3. Output: Correlation produces a correlation coefficient, which ranges from -1 to 1, indicating the strength and direction of the relationship. Regression produces an equation that can be used to predict the value of one variable based on the value of another variable.
4. Use of variables: In correlation, both variables are treated as independent and equal, while in regression, one variable is considered the independent variable (predictor) and the other is considered the dependent variable (outcome).
5. Interpretation: Correlation is used to determine if there is a relationship between two variables, while regression is used to quantify the relationship and make predictions based on that relationship.
0
