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Correlation and regression are two fundamental statistical techniques used to study the relationship between variables. Correlation measures the strength and direction of a linear relationship between two quantitative variables. The most commonly used measure is the Pearson correlation coefficient, denoted as *r*, which ranges from -1 to +1. * If *r = 1*, it indicates a perfect positive linear relationship. * If *r = -1*, it indicates a perfect negative linear relationship. * If *r = 0*, it indicates no linear relationship. For example, consider the data on hours studied (X) and marks obtained (Y) by five students: | Student | Hours Studied (X) | Marks Obtained (Y) | | ------- | ----------------- | ------------------ | _______ _____ __________ __________ ______ _________ _______ ______.
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