Correlation and Regression 1
This quiz is about MCQ on correlation and regression analysis.
This Section contains MCQs on Correlation Analysis, Simple Regression Analysis, Multiple Regression Analysis, Coefficient of Determination (Explained Variation), Unexplained Variation, Model Selection Criteria, Model Assumptions, Interpretation of results, Intercept, Slope, Partial Correlation, Significance tests, OLS Assumptions, Multicollinearity, Heteroscedasticity, Autocorrelation, etc. Let us start MCQ on Correlation and Regression Analysis
Correlation is a statistical measure used to determine the strength and direction of the mutual relationship between two quantitative variables. The regression describes how an explanatory variable is numerically related to the dependent variables.
Both of the tools are used to represent the linear relationship between the two quantitative variables. The relationship between variables can be observed either using graphical representation between the variables or numerical computation using appropriate computational formula.
Note that neither regression nor correlation analyses can be interpreted as establishing some cause-and-effect relationships. Both of these can be used to indicate only how or to what extent the variables under study are associated (or mutually related) with each other. The correlation coefficient measures only the degree (strength) and direction of linear association between the two variables. Any conclusions about a cause-and-effect relationship must be based on the judgment of the analyst.