Question

How is a linear regression analysis is different from a correlation analysis?

Answer 1

Answer:

The focuses given underneath, clarifies the contrast among correlation and regression in detail:

• A factual measure which decides the co-relationship or relationship of two amounts is known as Correlation. Regression portrays how a free or independent factor is numerically identified with the needy or dependent variable.
• Correlation is utilized to indicate to the direct / linear connection between two factors. Despite what might be expected, regression is utilized to fit the best line and gauge one variable based on another variable.
• In this Correlation, there is no distinction among needy/dependent and autonomous/independent factors for example correlation among's x and y is like y and x. On the other hand, the relapse/regression of y on x is not quite the same as x on y.
• Correlation demonstrates the quality of relationship between factors. Rather than, relapse mirrors the effect of the unit change in the autonomous variable on the needy variable.
• Correlation targets finding a numerical worth that communicates the connection between factors. Dissimilar to regression whose objective is to foresee estimations of the irregular variable based on the estimations of fixed variable.