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The correlation coefficient (often denoted as "r") quantifies the strength and direction of a linear relationship between two variables. A strong positive correlation (e.g., r = 0.9) indicates that as one variable increases, the other tends to increase as well. For instance, a high correlation between advertising spend and sales confirms their strong linear relationship, observed in the scatter plot. This metric is critical for assessing relationships before performing regression or predictive modeling. Why Other Options Are Wrong : A) Standard deviation measures variability, not relationships. C) Mean difference compares group averages, not correlations. D) P-value tests hypotheses but doesn’t quantify relationships. E) Variance measures the spread within a single variable, not between two.
The books supplied to the sections will be in the custody of the Assistant Audit Officers in charge of the sections.
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