3. Generate a five number summary for each of the quantitative variables. (3 pts) FebTemps Lincoln 11 35 42.5 53 73 S1 = min ( ) S2 = Q1 ( ) S3 = median ( ) S4 = Q3 ( ) $5 = max ( ) FebTemps San_Luis_Obispo 52 60 67 75.5 87 S1 = min $2 - Q1( S3 - median $4 - 03 $5 - max FebTemps FocusFebTemps Sedona 47 55 62 65 68 $1 = min () $2 = 01 ( ) $3 = median ( ) S4 = 03 ( ) $5 = max ( ) D Focus4. Create a boxplot for each quantitative variable (include boxplots in your Editing Voice Editor submission). Using the boxplots, determine the number of outliers (for each quantitative variable) present in each data set. (3 pts) FebTemps Box Plot 0 10 20 30 40 50 60 70 80 Lincoln FebTemps Box Plot 65 70 75 80 85 90 50 55 60 San_Luis_Obispo Focus Accessibility: Investigate 99+ NFebTemps Box Plot 50 55 60 65 70 Sedona D Focus WO 5. Using your responses from question 3 and 4 above, answer the following, a. The highest 25% of temperatures in Sedona are between what two values? b. The lowest 50% of temperatures in Lincoln are between what two values? c. The middle 50% of temperatures in San Luis Obispo are between what two values? (3 pt) 6. bility: Investigate D Focus O W DELL