Outliers have VERY LITTLE OR NO EFFECT on which of the following?
Outliers have very little or no effect on the following:
1. Median: The median is the middle value when data is arranged in ascending or descending order. Outliers have little impact on the median because it only considers the middle value, regardless of extreme values.
2. Mode: The mode is the value that appears most frequently in a dataset. Outliers have no impact on the mode because it is determined entirely by the frequency of values, rather than their actual numerical values.
3. Range: The range is the difference between the maximum and minimum values in a dataset. Outliers can have a significant impact on the range as they may greatly increase or decrease the maximum or minimum value.
4. Interquartile Range (IQR): The IQR is the range between the first quartile (25th percentile) and the third quartile (75th percentile) in a dataset. Outliers have minimal impact on the IQR since it considers the central 50% of the data, and extreme values do not affect the quartiles.
5. Percentiles: Percentiles indicate the value below which a given percentage of data falls. Outliers have very little effect on percentiles since they represent the relative standing within the distribution, and extreme values do not significantly alter the relative position of other data points.
6. Skewness: Skewness measures the asymmetry of a dataset's distribution. Outliers may have some influence on skewness, particularly if they are extreme and deviate significantly from the majority of the data points. However, the impact of outliers on skewness depends on their number and the specific characteristics of the data.
It is important to note that while outliers may have little effect on these statistical measures, they can still have a significant impact on other statistical analyses, such as regression analysis or hypothesis testing. Therefore, it is crucial to identify and handle outliers appropriately in these cases.