What does a regression analysis help to determine about the independent variable(s)?

A regression analysis primarily helps to determine the effect of independent variable(s) on the dependent variable. In this statistical method, the independent variable(s) are used to predict or explain changes in the dependent variable. The analysis provides coefficients that quantify the strength and direction of the relationship between these variables, allowing researchers to understand how variations in the independent variable(s) correlate with changes in the dependent variable.

For instance, in healthcare statistics, regression can be used to understand how factors such as age, weight, or treatment type influence patient outcomes. This insight is crucial for making informed decisions based on data and for identifying key predictors that can be addressed in healthcare interventions.

The other options, while related to data analysis, do not specifically pertain to what regression analysis is designed to achieve. Analyzing the mean value pertains to descriptive statistics, assessing the variation of data points relates to measures of dispersion, and normality of distribution involves understanding the shape of the dataset, none of which directly address the relationship between independent and dependent variables as regression does.