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How will the removal of the outliers affect the relationship between screen time and weight?

Diagram for question

Rationale

It will weaken the positive relationship.

The removal of outliers in a dataset typically reduces the impact of extreme values that can disproportionately influence the correlation between two variables. In this case, by eliminating outliers, the overall positive relationship between screen time and weight will likely become less pronounced.

A (It will weaken the positive relationship) CORRECT

Outliers can skew the correlation, making it appear stronger than it is. By removing these extreme values, the data may show a weaker positive correlation between screen time and weight, as the remaining data points will more accurately reflect the typical relationship without the influence of the outliers.

B (It will strengthen the positive relationship) YOUR ANSWER

Removing outliers usually does not strengthen a correlation; instead, it often leads to a more accurate representation of the relationship. If the outliers were driving a perceived strength in the correlation, their removal would likely diminish that effect rather than enhance it.

C (It will strengthen the negative relationship) YOUR ANSWER

This option is incorrect because the context of the question pertains to a positive relationship between screen time and weight. Removing outliers does not create a negative relationship; it simply adjusts the existing positive relationship, likely making it weaker rather than switching its direction.

D (It will weaken the negative relationship) YOUR ANSWER

Since there is no established negative relationship between screen time and weight in the context of this question, this option is not applicable. The focus is on the positive correlation, and outlier removal affects only that aspect, not a non-existent negative one.

Conclusion

In summary, the removal of outliers serves to clarify the actual relationship between screen time and weight by reducing the influence of extreme values. This action typically weakens any apparent positive correlation, allowing for a more accurate assessment of how these variables interact under normal conditions.

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