Final answer:
Outliers are data points that are significantly different from the other data points. They can be excluded or kept depending on their cause and relevance to the study. Statistical tests can be used to identify outliers.
Step-by-step explanation:
Outliers are data points that are significantly different from the other data points. They can be considered as bad data if they are errors or abnormalities. Here are some ways to deal with outliers:
- Exclude the outlier: If it is determined that the outlier is a result of incorrect data, it may be best to exclude it from the analysis.
- Keep the outlier: Sometimes, outliers can provide valuable information about the population being studied. In such cases, it is advisable to keep the outlier in the data.
- Analyze the cause: It is important to examine the cause of an outlier to understand why it deviates from the other data points. This analysis can help determine the appropriate action to take.
- Use statistical tests: There are various statistical tests, such as the Interquartile Range (IQR) or z-scores, that can be used to identify and handle outliers.