How can outliers impact the correlation coefficient?They can inflate the coefficient.They can deflate the coefficient.They can make the coefficient closer to zero.All of the above
Question
How can outliers impact the correlation coefficient?They can inflate the coefficient.They can deflate the coefficient.They can make the coefficient closer to zero.All of the above
Solution
Outliers can significantly impact the correlation coefficient in several ways:
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Inflation of the coefficient: If the outlier is in the same direction as the rest of the data, it can inflate the correlation coefficient. This means that the correlation appears stronger than it actually is.
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Deflation of the coefficient: Conversely, if the outlier is in the opposite direction of the rest of the data, it can deflate the correlation coefficient. This means that the correlation appears weaker than it actually is.
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Coefficient closer to zero: If the outlier is far from the line of best fit, it can pull the correlation coefficient closer to zero. This means that the correlation appears non-existent or much weaker than it actually is.
So, the correct answer is "All of the above". Outliers can inflate, deflate, or make the correlation coefficient closer to zero, depending on their values and positions in the data set.
Similar Questions
A local ice cream shop kept track of the number of cans of cold soda it sold each day, and the temperature that day, for two months during the summer. The data are displayed in the scatterplot below:The one outlier corresponds to a day on which the refrigerator for the soda was broken. Which of the following is true? A reasonable value of the correlation coefficient r for these data is 1.2. If the temperature were measured in degrees Celsius (C = 5/9*(F-32)), the value of r would change accordingly. If the outlier were removed, r would increase. If the outlier were removed, r would decrease.
The weights (in pounds) and cholesterol levels (in mg/dL) of several individuals was observed. The data are shown in the scatterplot below:The outlier on the graph is likely due to an error in recording the data. Which of the following statements is true? A reasonable value of the correlation coefficient r for these data is 1.2. If the weight (WT) were measured in kilograms instead of pounds (1 lb = 0.4536 kg) the value of r would change accordingly. If the outlier were removed, the correlation coefficient (r) would increase. If the outlier were removed, the correlation coefficient (r) would decrease.
How did the outlier affect the scores?
The correlation coefficient will always take values
Which of the following is not affected by outliers?
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