Samp.1 Samp.2 Samp.3
1 88 119 91
2 166 116 98
3 143 92 117
4 110 94 62
5 86 86 51
6 108 81 40
7 133 133 57
8 105 65 74
9 114 82 65
10 126 90 60
11 87 86 26
12 99 98 81
13 72 58 133
14 98 106 174
15 73 99 134
16 137 102 120
17 109 93 119
18 82 101 171
19 122 100 132
20 174 101 88
21 65 126 154
22 99 103 154
23 109 142 94
24 105 103 121
25 79 105 131
__________________________
Median 105 100 98
Mean 108 99 102
Based on the sample medians and means (last two rows of the table), the center estimates are fairly similar for the data sets, considering the noise level. So if we would only estimate center it would be hard to tell these data sets apart. But in this class PLOT DATA is a must! Comparison boxplots yield:
-------------
1 -------I + I-----------------
-------------
------
2 * * ---I + I------- * *
------
-----------------------
3 -------------I + I--------------
-----------------------
------+---------+---------+---------+---------+---------+C20
30 60 90 120 150 180
By the length of the boxes (i.e. interquartile ranges), we see that the noise levels are quite different in the data sets. Sample 3 seems to be twice as noisy as Sample 2 and Sample 2 seems to be twice as noisy as Sample 1. So along with measures of center we need measures of noise. For the third data set the boxplot misses something very important. From the stem leaf plot the data appears to be bimodal. The other two data sets appear to be unimodal.
Stem-and-leaf of Sample 1 N = 25
Leaf Unit = 1.0
1 6 5
4 7 239
8 8 2678
11 9 899
(5) 10 55899
9 11 04
7 12 26
5 13 37
3 14 3
2 15
2 16 6
1 17 4
Stem-and-leaf of Sample 2 N = 25
Leaf Unit = 1.0
1 5 8
2 6 5
2 7
6 8 1266
12 9 023489
(8) 10 01123356
5 11 69
3 12 6
2 13 3
1 14 2
Stem-and-leaf of Sample 3 N = 25
Leaf Unit = 10
1 0 3
3 0 45
8 0 66677
12 0 8999
(1) 1 0
12 1 22223333
4 1 55
2 1 77
Again: you must PLOT the data and it is best to use several different different types of plots. What do the comparison boxplots tell you (5 extra brownie points)?