Correlation Vs Regression

While correlation uses a single coefficient to represent the strength and direction of the association, regression formulates an equation to provide deeper insights and forecasting capabilities.


  • Shows the association of 2 variables.
  • Displays liner relationships between 2 variables.
  • No difference between dependent & Independent variables
  • Resembles the strength of association.
  • Aim’s to find the numerical values helps show the relationship.


  • Shows how independent variable is numerically related to dependent variable.
  • Liner Regression fits best , Helps estimate one variables basis on another variables.
  • The regression of y on x is different from x on y .
  • Regression reflects the impact of the units changes in the independent variables on the dependent variable.
  • Regression whose goal is to predict values of the random variable on the basis of the values of fixed variable.

Similarities between correlation and regression

Thought having some key difference between correlation & regression, there are some similarities.

  • Both works to express the direction & strength of relationship between 2 variables.
  • When correlation is negative the regression slide/slope is also negative.
  • When correlation is positive the regression slide/ line is also positive.
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Saniya Gazala

Saniya Gazala is a Computer Science graduate from Reva University. She began as a manual tester, honing her skills in defect identification and problem-solving. Transitioning to technical writing, she simplified complex tech concepts for users. Her journey is marked by continuous learning and growth in the tech industry.

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