Question

Identify a situation where using correlation coefficient is appropriate. Could a regression equation be used in the same situation? How are correlation and regression alike? How are they different?

Answer 1

Answer;

Regression is primarily used to build models/equations to predict a key response, Y, from a set of predictor (X) variables. Correlation is fundamentally  utilized  to quickly and concisely summarize the direction and strength of the relationships between a set of two  or more nuemeric variables.

The main difference between correlation and regression is that in correlation, you sample both estimation factors  randomly from a population, while in regression you pick  the estimations  of the independent (X) variable.

Differences between correlation and regression:

Correlation:

• Correlation gives the strong relationship between two or more variable without knowing functional relationship.
• Correlation is unit less.
• Correlation does not depends on choosing the variables.

Regression:

• Regression shows the functional relation between one independent variable with other dependent variable.
• The Regression line has same unit.
• Regression gives the relation between dependent and independent variable.