Final answer:
There are no apparent outliers in the first and third sets of numbers. The second set, with the number 30, may contain an outlier. Outliers can be determined using the IQR method or by checking if data points lie beyond two standard deviations from the mean.
Step-by-step explanation:
To determine if there are any outliers in the given sets of numbers, we can use the Interquartile Range (IQR) method or examine if any data points are more than two standard deviations away from the mean. The IQR is the difference between the third quartile (Q3) and the first quartile (Q1) of the dataset. Any data point that lies beyond 1.5 * IQR above the third quartile or below the first quartile is considered an outlier.
- For the first set of numbers (12, 14, 15), the values are all close to each other, suggesting no outliers.
- For the second set (12, 14, 30), the number 30 seems significantly higher than the rest, which may suggest it's an outlier.
- For the third set (12, 14, 15, 16), the values are similar to the first set, with no obvious outliers.
In the second set, if 30 is confirmed as an outlier based on the IQR or standard deviation method, a decision would need to be made about how to handle it. Depending on the analysis or data usage, options include keeping the outlier, removing it, or using robust statistical methods less sensitive to outliers.