QUESTION IMAGE
Question
two sets of data are graphed here. they are identical, except for the addition of point q in the second set. if their correlation coefficients are ( r_1 ) (for the first set) and ( r_2 ) (for the second set), choose the correct statement. a ( r_1 < r_2 ) b ( r_2 < r_1 ) c ( r_1 = r_2 ) d ( r_1 + r_2 > 0 )
Brief Explanations
- Recall the concept of correlation coefficient: It measures the strength and direction of a linear relationship between two variables. A negative correlation means as one variable increases, the other tends to decrease, and the closer the correlation coefficient is to -1, the stronger the negative linear relationship.
- Analyze the first data set: The points show a negative linear trend (as x increases, y decreases).
- Analyze the second data set (with point Q): Point Q appears to be an outlier or a point that weakens the negative linear trend. When we add a point that is less in line with the negative trend, the correlation coefficient (which was negative for the first set) becomes less negative (closer to 0) or maybe even less negative than the first one. Wait, no—wait, actually, the first set has a stronger negative trend. When we add point Q, which is above the general trend line of the first set (since in the second graph, Q is a point that is more towards the positive y for a given x compared to the first set's points), so the second set's correlation is less negative (i.e., closer to 0) than the first set's. But since both are negative (because the overall trend is negative), \( r_1 \) (first set) is more negative (smaller) than \( r_2 \) (second set). So \( r_2>r_1 \) (because a number closer to 0 is larger than a more negative number; e.g., -0.8 < -0.5, so if \( r_1=-0.8 \) and \( r_2 = -0.5 \), then \( r_2>r_1 \)). Wait, but the options: Option B is \( r_2 < r_1 \)? No, wait, maybe I got it reversed. Wait, let's think again. The first set: the points are more tightly clustered in a negative slope. The second set, with point Q, which is a point that is "out of line"—it's a point that is above the line of best fit for the first set. So adding Q makes the correlation weaker (less negative, i.e., closer to 0). So \( r_1 \) (first set) is more negative (smaller value) than \( r_2 \) (second set, which is less negative, so larger value). So \( r_2>r_1 \), which means \( r_1 < r_2 \)? Wait, no—wait, correlation coefficients: if the trend is negative, \( r \) is negative. A stronger negative trend (more tightly clustered) has \( r \) closer to -1. A weaker negative trend (more spread out or with an outlier) has \( r \) closer to 0. So first set: more tightly clustered negative trend, so \( r_1 \) is closer to -1 (more negative). Second set: with Q, which is an outlier that makes the trend less strong, so \( r_2 \) is closer to 0 (less negative). So \( r_1 \) (more negative) is less than \( r_2 \) (less negative). So \( r_1 < r_2 \)? Wait, but the options: Option A is \( r_1 < r_2 \), Option B is \( r_2 < r_1 \). Wait, maybe I made a mistake. Wait, let's take numbers. Suppose first set has \( r_1 = -0.9 \) (strong negative). Second set, adding Q, which is a point that is not following the trend, so \( r_2 = -0.6 \). Then \( -0.9 < -0.6 \), so \( r_1 < r_2 \). So Option A would be correct? Wait, but let's check the graphs. The first graph: points are more in a line with negative slope. The second graph: same points plus Q, which is a point that is above the line (so for a given x, y is higher than the first set's points at that x). So adding Q makes the correlation less strong (less negative), so \( r_2 \) is greater than \( r_1 \) (since -0.6 > -0.9). So \( r_1 < r_2 \), which is Option A? Wait, no—wait, the options: A is \( r_1 < r_2 \), B is \( r_2 < r_1 \), C is \( r_1 = r_2 \), D is \( r_1 + r_2 > 0 \). But since both are negative (because the trend is negative), their sum would be negative (e.g., -0.9 + (-0.6) = -1.5 < 0),…
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A. \( r_1 < r_2 \)