The example inclues dataset containing species composition of microorganisms isolated from 68 dentistry patients. Presence of microbe is designated as ‘1’, absence – ‘0’. Thus, the dataset contains binary data. Discussion of this example is done in Nonparametric correlation.
Composition of oral microflora in patients with parasitic invasions of gastrointestinal tract
|
№ of patient
|
S.epidermidis
|
S.aureus
|
Lactobacillus spp.
|
C.albicans
|
E.coli
|
S.pyogenes
|
S.mitis
|
|
1
|
1
|
1
|
1
|
1
|
0
|
1
|
1
|
|
2
|
1
|
0
|
1
|
1
|
0
|
1
|
1
|
|
3
|
0
|
0
|
0
|
1
|
1
|
1
|
1
|
|
4
|
1
|
0
|
1
|
1
|
0
|
1
|
1
|
|
5
|
1
|
0
|
1
|
1
|
0
|
1
|
1
|
|
6
|
0
|
0
|
1
|
1
|
1
|
1
|
1
|
|
7
|
1
|
0
|
1
|
0
|
0
|
1
|
1
|
|
8
|
0
|
1
|
0
|
1
|
0
|
1
|
1
|
|
9
|
0
|
1
|
1
|
0
|
0
|
1
|
0
|
|
10
|
1
|
1
|
1
|
1
|
0
|
1
|
0
|
|
11
|
1
|
1
|
1
|
1
|
0
|
1
|
0
|
|
12
|
1
|
1
|
1
|
0
|
1
|
1
|
1
|
|
13
|
1
|
1
|
1
|
0
|
0
|
1
|
1
|
|
14
|
0
|
0
|
0
|
1
|
1
|
1
|
1
|
|
15
|
1
|
0
|
1
|
0
|
0
|
1
|
1
|
|
16
|
1
|
0
|
1
|
0
|
0
|
0
|
1
|
|
17
|
1
|
0
|
1
|
1
|
1
|
0
|
1
|
|
18
|
1
|
0
|
1
|
1
|
0
|
0
|
1
|
|
19
|
1
|
0
|
1
|
0
|
0
|
0
|
0
|
|
20
|
0
|
1
|
1
|
0
|
0
|
1
|
0
|
|
21
|
1
|
0
|
1
|
0
|
0
|
1
|
1
|
|
22
|
1
|
0
|
1
|
0
|
1
|
0
|
1
|
|
23
|
1
|
0
|
1
|
1
|
0
|
1
|
1
|
|
24
|
1
|
1
|
1
|
1
|
1
|
1
|
1
|
|
25
|
1
|
1
|
1
|
1
|
0
|
1
|
1
|
|
26
|
0
|
0
|
1
|
1
|
1
|
1
|
1
|
|
27
|
1
|
1
|
1
|
1
|
0
|
1
|
1
|
|
28
|
0
|
1
|
1
|
0
|
0
|
0
|
0
|
|
29
|
0
|
1
|
1
|
0
|
0
|
1
|
1
|
|
30
|
0
|
0
|
0
|
1
|
0
|
0
|
0
|
|
31
|
1
|
1
|
1
|
0
|
1
|
1
|
0
|
|
32
|
1
|
0
|
0
|
1
|
0
|
0
|
0
|
|
33
|
1
|
1
|
1
|
0
|
0
|
1
|
1
|
|
34
|
1
|
0
|
1
|
1
|
1
|
0
|
1
|
|
35
|
1
|
0
|
1
|
0
|
1
|
1
|
1
|
|
36
|
0
|
1
|
1
|
0
|
0
|
1
|
0
|
|
37
|
0
|
1
|
1
|
0
|
0
|
0
|
0
|
|
38
|
1
|
0
|
1
|
1
|
1
|
0
|
1
|
|
39
|
1
|
0
|
0
|
1
|
1
|
0
|
1
|
|
40
|
0
|
0
|
0
|
0
|
0
|
1
|
0
|
|
41
|
0
|
1
|
1
|
1
|
0
|
1
|
0
|
|
42
|
0
|
1
|
1
|
0
|
0
|
0
|
0
|
|
43
|
0
|
0
|
1
|
0
|
0
|
1
|
0
|
|
44
|
1
|
0
|
1
|
0
|
0
|
0
|
1
|
|
45
|
0
|
1
|
1
|
0
|
0
|
0
|
0
|
|
46
|
0
|
1
|
1
|
0
|
0
|
1
|
0
|
|
47
|
0
|
1
|
1
|
0
|
0
|
1
|
1
|
|
48
|
1
|
0
|
0
|
0
|
0
|
1
|
0
|
|
49
|
1
|
1
|
1
|
0
|
1
|
0
|
0
|
|
50
|
1
|
0
|
1
|
1
|
0
|
1
|
1
|
|
51
|
1
|
1
|
0
|
1
|
0
|
1
|
1
|
|
52
|
1
|
0
|
1
|
0
|
0
|
0
|
0
|
|
53
|
0
|
1
|
1
|
0
|
0
|
1
|
0
|
|
54
|
0
|
0
|
1
|
0
|
0
|
0
|
0
|
|
55
|
1
|
0
|
1
|
0
|
1
|
0
|
0
|
|
56
|
1
|
0
|
0
|
1
|
0
|
0
|
0
|
|
57
|
1
|
0
|
0
|
0
|
0
|
1
|
1
|
|
58
|
0
|
1
|
0
|
0
|
0
|
1
|
0
|
|
59
|
1
|
0
|
1
|
0
|
0
|
1
|
0
|
|
60
|
1
|
0
|
1
|
1
|
0
|
1
|
0
|
|
61
|
1
|
0
|
1
|
1
|
0
|
1
|
0
|
|
62
|
0
|
0
|
0
|
1
|
0
|
0
|
0
|
|
63
|
0
|
0
|
0
|
0
|
0
|
1
|
0
|
|
64
|
1
|
0
|
0
|
1
|
1
|
0
|
0
|
|
65
|
1
|
1
|
1
|
0
|
0
|
1
|
0
|
|
66
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
|
67
|
0
|
0
|
1
|
0
|
0
|
1
|
0
|
|
68
|
1
|
0
|
1
|
1
|
0
|
1
|
1
|
