Points possible a. In your own words, describe to someone who knows only a little statistics how to recognize when an observation is an outlier. What action(s) should be taken with an outlier? b. Which measure of the center (mean or median) is more resistant to outliers, and what does "resistant to outliers" mean? a. Choose the best answer below. OA. Outliers are observations that are more than 1.5 interquartile ranges from the median in a data set. They should be looked at in closer context to determine how to treat the values. Sometimes they may be included, but sometimes they are discarded. OB. Outliers are observed values far from the main group of data. In a histogram they are separated from the others by space. Outliers should be ignored because they can distort any calculations done and are not representative of typical values. O C. Outliers are observed values far from the main group of data. In a histogram they are separated from the others by space. Outliers must be looked at in closer context to know how to treat them. If they are mistakes, they might be removed or corrected. If they are not mistakes, you might do the analysis twice, once with and once without the outliers. OD. Outliers are the minimum and maximum values observed in a data set. They should be treated as any other value, as the term "outliers" is just another name for the minimum and maximum. b. Choose the best answer below. OA. The mean is more resistant, which indicates that it is easier to calculate when there are outliers present than the median is. OB. The median is more resistant, which indicates that neither the number nor the magnitude of outliers has any effect on the calculated value of the median. OC. The mean is more resistant, which indicates that it usually changes less than the median when comparing data with and without outliers. OD. The median is more resistant, which indicates that it usually changes less than the mean when comparing data with and without outliers.