Here is your (discrete) data 108 83 93 118 88 58 88 65 113 103 119...

Here is your (discrete) data 108 83 93 118 88 58 88 65 113 103 119 101 91 92 95 86 85 73 94 61 121 71 116 78 114 119 118 131 41 70 68 98 202 155 41 93 78 96 93 110 100 61 98 39 94 86 108 75 64 50 90 123 109 69 118 85 102 86 153 109 89 134 80 104 96 129 48 81 102 31 97 130 98 105 109 77 113 62 80 99 First, sort the data. Second, build a GFDT for this table with a classwidth of 15. (Be sure your lower class limits are multiples of the classwidth.) Next, answer the following questions about the data set: 1. What is the first lower class limit in your GFDT (given the classwidth of 15)? 2. Express the fourth class as a closed interval, i.e., [ a , b ] [a,b] . 3. Give the frequency for the fourth class. 4. What is the (arithmetic) mean for this data (report accurate to one decimal place)? 5. Using the GFDT, what is the mode for this data set (Hint: Create the Frequency table first, then determine the class with the highst frequency. The mode is the middle of that class, that is (Upper class limit+Lower class Limit)/2)? Another hint ([90,104]is the class with the highest frequency) 6. What is the standard deviation for this data (report accurate to two decimal places)? 7. What is the five number summary for this data set (separate numbers with a comma)? 8. What is the IQR? 9. What usual score (i.e., non-outlier) has the largest positive z-score less than z = 2 z=2 ? (Give the data value, not the z-score.) 10. Give the fences---this would suggest something other than z-scores---for the mild outliers at the maximal end of the data set; report as a closed interval, i.e., [upper mild fence, upper extreme fence](Hint: UMF=Q3+1.5*IQR, UEF=Q3+3*IQR)