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Q: When can I use correlation analysis as opposed to regression analysis?
I would like to test a number of hypotheses but I am not sure which analysis method is best. I am therefore looking for information indicating instances when to use each method, including interpretation and reporting of results. Can you suggest suitable resources? I am new to research work.
The usage of correlation analysis or regression analysis depends on your data set and the objective of the study. Correlation analysis is used to quantify the degree to which two variables are related. Through the correlation analysis, you evaluate correlation coefficient that tells you how much one variable changes when the other one does. Correlation analysis provides you with a linear relationship between two variables.
Regression analysis is a related technique to assess the relationship between an outcome variable and one or more risk factors or confounding variables. The outcome variable is also called the response or dependent variable and the risk factors and confounders are called the predictors, or independent variables. Regression analysis is useful when you have to identify the impact of a unit change in the known variable (x) on the estimated variable (y).
If you need further help with conducting the statistical analysis, you might find benefit in availing to a professional publication support services, for example, Editage’s Statistical Review Service.
Related reading:
Importance of statistical power in research design
How do I reply to a reviewer's comment about my logistic regression analysis?
This content belongs to the Conducting Research Stage