Outliers and side-by-side boxplots:Outliers are "extreme observations" for a set of data, but how does one determine what is extreme? Boxplots help us in identifying such observations, and side-by-side boxplots are very useful when we want to display quantitative data across levels of a categorical variable, e.g. heights by gender. Create the side-by-side boxplots for Height by Gender. Click Graph > Boxplot > With Groups. Select Heights for the "Graph Variables" and Gender for the "Categorical Variables" and click OK. Copy and uploadyour graph below and answer the following questions related to the graph:

A)The '*' symbol in the boxplots represents an outlier. By placing your mouse over this symbol in Minitab you can determine what the outlier value is and the data row in which it is located. What are the values and data rows for the Male outliers? B) How these observation were determined as outliers? Calculate the lower and upper "fence" points and apply this technique to demonstrate why this observation would be considered an outlier. C) In comparing the two boxplots, how would you describe the center and spread of the heights by gender? More specifically, which gender has the greater mean height and median height, and what about variability, specifically the standard deviation?

Group: Gender = M Q1 = 68 Median = 70 Q3 = 71 IQRange = 3 Whiskers to: 66, 75 N = 32