Final answer:
The first step with potential outliers is to investigate further, which involves careful evaluation to ascertain whether they provide valuable insights or indicate errors in the dataset. Option D
Step-by-step explanation:
When confronted with potential outliers in a dataset, the first step is not to eliminate or make assumptions about these data points hastily. Instead, the correct course of action is D. Investigate further. Outliers may provide valuable insights or indicate errors; thus, careful evaluation is essential.
This evaluation can involve checking for data entry mistakes, considering the possibility of sampling errors, or recognizing that the outlier represents a true variation within the data.
Potential outliers should be examined with appropriate statistical tests, like those involving the Interquartile Range (IQR), to determine their legitimacy.
It is only after a thorough investigation that a decision can be made on whether to keep or remove an outlier from the analysis. If an outlier is due to a data recording error or it significantly distorts the analysis, it might be excluded. Otherwise, it should be included to ensure a complete and accurate representation of the data. Option D