QUESTION 12 Outliers (z-scores) Outliers are points that are `further away" from the other data points or possibly ``further away" from the trend or pattern for the other data. The precise line used...

3.0 OR of Z < -="" 3.0="" would="" clearly="" be="" in="" the="" range="" for="" outliers.="" [see="" empirical="" rule="" later.]="" suppose="" a="" set="" of="" data="" is="" mound-shaped="" and="" has="" a="" mean="" of="" 72="" and="" standard="" deviation="" of="" o="8.0." {="" (mu)="72," (sigma)="8.0" }="" for="" each="" of="" the="" following="" data="" points,="" find="" the="" z-score="" and="" classify="" whether="" the="" point="" should="" be="" considered="" an="" outlier.="" a)="" xi="93" b)="" xi="98" c)="" xi="45" d)="" xi="52" "/="">
Extracted text: QUESTION 12 Outliers (z-scores) Outliers are points that are `further away" from the other data points or possibly ``further away" from the trend or pattern for the other data. The precise line used for determining what is ' further away" is sometimes subject to judgement and can vary depending on context and goals. [NOTE: Not every data set will have outliers.] One means of measuring to determine where the outliers are is use of the Z-score (the number of standard deviations away from the center). If the data is mound-shaped (largest amount concentrated near the middle), then a Z-score of Z> 3.0 OR of Z < -="" 3.0="" would="" clearly="" be="" in="" the="" range="" for="" outliers.="" [see="" empirical="" rule="" later.]="" suppose="" a="" set="" of="" data="" is="" mound-shaped="" and="" has="" a="" mean="" of="" 72="" and="" standard="" deviation="" of="" o="8.0." {="" (mu)="72," (sigma)="8.0" }="" for="" each="" of="" the="" following="" data="" points,="" find="" the="" z-score="" and="" classify="" whether="" the="" point="" should="" be="" considered="" an="" outlier.="" a)="" xi="93" b)="" xi="98" c)="" xi="45" d)="" xi="">