Question

1. Correlation analysis is used to determine

a. the equation of the regression line
b. a specific value of the dependent variable for a given value of the independent variable
c. the strength of the relationship between the dependent and the independent variables
d. None of these alternatives is correct.

Answer 1

Correlation analysis is used to determine the strength of the relationship between the dependent and independent variables in a dataset.

Step-by-step explanation:

The purpose of correlation analysis is to determine the strength of the relationship between the dependent and independent variables in a dataset.

For example, if we have a dataset that contains the hours studied by students and their corresponding test scores, correlation analysis can help us understand if there is a linear relationship between the hours studied and the test scores.

The correlation coefficient, which ranges from -1 to 1, quantifies the strength and direction of the relationship. A correlation coefficient close to 1 indicates a strong positive relationship, close to -1 indicates a strong negative relationship and close to 0 indicates no relationship.

Answer 2

b. a specific value of the dependent variable for a given value of the independent variable

Step-by-step explanation:

In correlation analysis, one can measure the strength of the relationship between two or more variables.

The aim of this analysis is to understand that in case of any change in the independent variable there is also change in the dependent variable or not.

The most common correlation method used is Pearson correlation, which measures linear relationships between variables.