A marketing analyst at a clothing retailer tracks daily store foot traffic and daily revenue. The analyst wants to find a technique that captures how these two numbers vary together in a linear pattern. Which method is appropriate for this?
Calculating a correlation coefficient is the accepted way to measure how strongly two continuous variables increase or decrease together. This captures the linear relationship between daily foot traffic and revenue. A chi-squared test evaluates categorical data distributions rather than continuous figures. A regression intercept focuses on the value where a regression line crosses the axis without describing how tightly the variables move together. A daily range difference calculates the gap between high and low values but does not quantify how two sets of numbers relate.
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What is a correlation coefficient and how is it calculated?
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What is the difference between correlation and regression?
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In what scenarios is a chi-squared test used instead of correlation?