Question

To find an outlier at the bottom of the distribution, I need to know the mean the 25 th percentile the 75 th percentile the upper limit outlier

Answer 1

To find an outlier at the bottom of the distribution, you need to know the lower limit.

Step-by-step explanation:

Identifying outliers in a distribution involves understanding the spread and central tendency of the data. The lower limit is crucial in determining outliers at the bottom of the distribution. An outlier is typically defined as a data point that falls significantly below or above the central bulk of the data.

To identify an outlier at the bottom, consider the lower limit. This limit is often calculated using the interquartile range (IQR), which is the difference between the 75th percentile (Q3) and the 25th percentile (Q1). The lower limit is given by
`\(Q1 - 1.5 * \text{IQR}\)`. Any data point below this lower limit is considered a potential outlier at the bottom.

Knowing the mean and percentiles (25th and 75th) can provide additional context to the distribution, but the crucial factor for identifying an outlier at the bottom is understanding the lower limit. It acts as a threshold, helping to differentiate between values within the normal range and those that may be considered outliers.