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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_hierarchicalclustering.wasp
Title produced by softwareHierarchical Clustering
Date of computationTue, 11 Nov 2008 12:41:35 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Nov/11/t1226432582h0f13jl8hx5cler.htm/, Retrieved Sun, 19 May 2024 11:36:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23892, Retrieved Sun, 19 May 2024 11:36:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Hierarchical Clustering] [Q2] [2008-11-11 19:41:35] [787873b6436f665b5b192a0bdb2e43c9] [Current]
Feedback Forum
2008-11-14 10:25:51 [Tamara Witters] [reply] 
Met deze clusteringtechniek gaat men zien welke observaties als gemeenschappelijk kunnen gezien worden in een bepaalde periode. In dit geval vallen de observaties in 2 groepen en deze groepen zijn telkens nog eens onderverdeeld in verschillende categorieën tot men op 1 observatie komt. Meestal gebruikt men deze techniek voor niet-tijdreeksen vb: hulpmiddel voor de marketing (vb marktsegmentatie).
2008-11-23 20:01:26 [df2ed12c9b09685cd516719b004050c5] [reply] 
Het dendogram wordt meestal gebruikt voor niet-tijdreeksen vb: in de marketing, om producten die samen horen te categoriseren.
Het dendogram geeft een clustering weer van observaties (maanden), er staat ook telkens een volgnummer bij. Welke observaties van de tijdreeksen gelijkaardig zijn, worden geclusterd, vormen dus aparte takken. Des te minder clusters er gevormd worden, des te meer verband in de tijdreeksen.
Hier zien we weinig clusters.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.95	13.92	15.22	1.1608
0.98	13.22	14.28	1.1208
1.23	13.31	14.61	1.0883
1.17	12.91	14.19	1.0704
0.84	13.19	14.02	1.0628
0.74	12.92	14.22	1.0378
0.65	13.43	14.80	1.0353
0.91	13.72	15.05	1.0604
1.19	13.97	15.24	1.0501
1.30	14.91	15.85	1.0706
1.53	14.46	15.43	1.0338
1.94	14.12	15.41	1.011
1.79	14.23	15.53	1.0137
1.95	15.04	15.95	0.9834
2.26	14.80	15.72	0.9643
2.04	14.49	15.68	0.947
2.16	15.14	16.06	0.906
2.75	14.34	15.27	0.9492
2.79	15.12	16.01	0.9397
2.88	15.14	15.44	0.9041
3.36	14.34	15.47	0.8721
2.97	14.36	15.49	0.8552
3.10	14.91	15.38	0.8564
2.49	15.56	16.62	0.8973
2.20	16.50	17.25	0.9383
2.25	15.57	16.37	0.9217
2.09	15.14	16.14	0.9095
2.79	15.19	15.76	0.892
3.14	15.07	15.54	0.8742
2.93	14.48	15.46	0.8532
2.65	14.27	15.26	0.8607
2.67	14.72	16.02	0.9005
2.26	14.65	15.67	0.9111
2.35	14.38	15.67	0.9059
2.13	13.95	15.48	0.8883
2.18	14.85	16.07	0.8924
2.90	14.87	16.65	0.8833
2.63	14.83	16.18	0.87
2.67	15.03	16.55	0.8758
1.81	15.47	16.58	0.8858
1.33	16.21	17.73	0.917
0.88	16.55	17.94	0.9554
1.28	17.04	18.66	0.9922
1.26	17.22	18.73	0.9778
1.26	17.47	19.07	0.9808
1.29	17.75	19.48	0.9811
1.10	17.84	19.52	1.0014
1.37	18.47	19.60	1.0183
1.21	18.38	20.32	1.0622
1.74	18.55	19.84	1.0773
1.76	18.39	19.81	1.0807
1.48	18.88	20.64	1.0848
1.04	20.21	22.12	1.1582
1.62	19.67	21.50	1.1663
1.49	20.09	21.77	1.1372
1.79	18.78	20.29	1.1139
1.8	19.74	21.76	1.1222
1.58	20.64	22.35	1.1692
1.86	20.34	22.15	1.1702
1.74	21.75	23.83	1.2286
1.59	22.10	24.46	1.2613
1.26	22.81	25.13	1.2646
1.13	22.91	24.36	1.2262
1.92	22.46	24.45	1.1985
2.61	21.78	23.66	1.2007
2.26	25.05	25.97	1.2138
2.41	23.70	25.20	1.2266
2.26	23.02	24.41	1.2176
2.03	24.34	25.32	1.2218
2.86	24.15	26.36	1.249
2.55	25.85	28.03	1.2991
2.27	26.42	28.95	1.3408
2.26	26.54	27.25	1.3119
2.57	26.36	27.47	1.3014
3.07	26.99	28.75	1.3201
2.76	27.52	29.24	1.2938
2.51	26.63	28.03	1.2694
2.87	26.26	27.34	1.2165
3.14	24.86	26.47	1.2037
3.11	26.84	28.30	1.2292
3.16	26.57	27.90	1.2256
2.47	24.67	26.69	1.2015
2.57	27.24	28.31	1.1786
2.89	27.77	28.84	1.1856
2.63	27.61	28.56	1.2103
2.38	27.27	28.25	1.1938
1.69	28.46	28.93	1.202
1.96	26.97	28.22	1.2271
2.19	29.95	31.77	1.277
1.87	29.88	31.64	1.265
1.6	29.67	30.60	1.2684
1.63	31.19	32.34	1.2811
1.22	30.24	31.51	1.2727
1.21	30.03	31.39	1.2611
1.49	31.02	32.19	1.2881
1.64	30.45	33.11	1.3213
1.66	31.70	33.99	1.2999
1.77	32.10	34.30	1.3074
1.82	32.32	34.53	1.3242
1.78	32.18	33.67	1.3516
1.28	33.43	34.72	1.3511
1.29	33.07	34.91	1.3419
1.37	35.32	36.24	1.3716
1.12	35.17	37.47	1.3622
1.51	35.29	36.94	1.3896
2.24	37.89	38.55	1.4227
2.94	38.32	39.88	1.4684
3.09	37.07	37.78	1.457
3.46	39.77	40.09	1.4718
3.64	39.20	40.17	1.4748
4.39	40.46	40.67	1.5527
4.15	44.95	44.82	1.5751
5.21	41.69	40.89	1.5557
5.80	41.88	41.47	1.5553
5.91	45.86	44.67	1.577

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23892&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23892&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23892&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Summary of Dendrogram
LabelHeight
10.106359061673185
20.130015383705161
30.151103441390327
40.164047432165213
50.166823979091737
60.194698125311981
70.20057479901523
80.202066919608331
90.214969974647624
100.221375902030912
110.230470909227172
120.242352140489823
130.263960773600929
140.266550182892457
150.269730402439176
160.297584021748480
170.302430157226425
180.321509624765963
190.322617792441771
200.326871243764269
210.331646212099580
220.333947419693491
230.347556268825639
240.352289667745166
250.352624446117962
260.361754435632208
270.379893993398211
280.398566820818928
290.407289381153006
300.414982035755767
310.427641318133964
320.439867356465921
330.456509583689107
340.462435323574999
350.479006064679771
360.484626464403255
370.492487400854072
380.51940242797056
390.54748287836312
400.549651531785766
410.591500540997217
420.603054359075532
430.603082913039327
440.61284294108708
450.618978553660433
460.624266769898895
470.658144543394534
480.664487399195191
490.667022068600433
500.669440632169874
510.674934145457615
520.727946999183924
530.730243349936725
540.730345698967277
550.74675089846669
560.753938352917532
570.75851835060794
580.783727763360603
590.788209718285686
600.848881711429808
610.886864378884209
620.887399802794659
630.935656853372118
640.975563492224267
651.03362387951607
661.09398098423581
671.09607656851168
681.13832573561032
691.16923159514141
701.24662930726834
711.27195591963656
721.31308665225943
731.35239055059429
741.36169179033375
751.4103107778075
761.42933334813494
771.45098935865143
781.48278438317301
791.56408277757764
801.56709869387710
811.57032965713959
821.59706817663672
831.60959973843666
841.66455517817392
851.67241035176915
861.81412981524401
871.87081099830136
881.98700870909012
892.15015381337444
902.46048985054225
912.46405050991360
922.4849740758858
932.62960882876486
943.05979310759203
953.10992522974607
963.82162364058846
974.69421170334864
984.78574256580058
995.29631894115553
1005.59275256541108
1016.62690103042577
1029.27136620920313
10310.035517504093
10412.0429495234857
10512.3153905114848
10619.1206115664269
10721.5471376838011
10821.9887629586038
10925.3853969310361
11047.8250361975686
111101.429906185177
112110.269511702147
113237.876729330625
114790.268378518266

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 0.106359061673185 \tabularnewline
2 & 0.130015383705161 \tabularnewline
3 & 0.151103441390327 \tabularnewline
4 & 0.164047432165213 \tabularnewline
5 & 0.166823979091737 \tabularnewline
6 & 0.194698125311981 \tabularnewline
7 & 0.20057479901523 \tabularnewline
8 & 0.202066919608331 \tabularnewline
9 & 0.214969974647624 \tabularnewline
10 & 0.221375902030912 \tabularnewline
11 & 0.230470909227172 \tabularnewline
12 & 0.242352140489823 \tabularnewline
13 & 0.263960773600929 \tabularnewline
14 & 0.266550182892457 \tabularnewline
15 & 0.269730402439176 \tabularnewline
16 & 0.297584021748480 \tabularnewline
17 & 0.302430157226425 \tabularnewline
18 & 0.321509624765963 \tabularnewline
19 & 0.322617792441771 \tabularnewline
20 & 0.326871243764269 \tabularnewline
21 & 0.331646212099580 \tabularnewline
22 & 0.333947419693491 \tabularnewline
23 & 0.347556268825639 \tabularnewline
24 & 0.352289667745166 \tabularnewline
25 & 0.352624446117962 \tabularnewline
26 & 0.361754435632208 \tabularnewline
27 & 0.379893993398211 \tabularnewline
28 & 0.398566820818928 \tabularnewline
29 & 0.407289381153006 \tabularnewline
30 & 0.414982035755767 \tabularnewline
31 & 0.427641318133964 \tabularnewline
32 & 0.439867356465921 \tabularnewline
33 & 0.456509583689107 \tabularnewline
34 & 0.462435323574999 \tabularnewline
35 & 0.479006064679771 \tabularnewline
36 & 0.484626464403255 \tabularnewline
37 & 0.492487400854072 \tabularnewline
38 & 0.51940242797056 \tabularnewline
39 & 0.54748287836312 \tabularnewline
40 & 0.549651531785766 \tabularnewline
41 & 0.591500540997217 \tabularnewline
42 & 0.603054359075532 \tabularnewline
43 & 0.603082913039327 \tabularnewline
44 & 0.61284294108708 \tabularnewline
45 & 0.618978553660433 \tabularnewline
46 & 0.624266769898895 \tabularnewline
47 & 0.658144543394534 \tabularnewline
48 & 0.664487399195191 \tabularnewline
49 & 0.667022068600433 \tabularnewline
50 & 0.669440632169874 \tabularnewline
51 & 0.674934145457615 \tabularnewline
52 & 0.727946999183924 \tabularnewline
53 & 0.730243349936725 \tabularnewline
54 & 0.730345698967277 \tabularnewline
55 & 0.74675089846669 \tabularnewline
56 & 0.753938352917532 \tabularnewline
57 & 0.75851835060794 \tabularnewline
58 & 0.783727763360603 \tabularnewline
59 & 0.788209718285686 \tabularnewline
60 & 0.848881711429808 \tabularnewline
61 & 0.886864378884209 \tabularnewline
62 & 0.887399802794659 \tabularnewline
63 & 0.935656853372118 \tabularnewline
64 & 0.975563492224267 \tabularnewline
65 & 1.03362387951607 \tabularnewline
66 & 1.09398098423581 \tabularnewline
67 & 1.09607656851168 \tabularnewline
68 & 1.13832573561032 \tabularnewline
69 & 1.16923159514141 \tabularnewline
70 & 1.24662930726834 \tabularnewline
71 & 1.27195591963656 \tabularnewline
72 & 1.31308665225943 \tabularnewline
73 & 1.35239055059429 \tabularnewline
74 & 1.36169179033375 \tabularnewline
75 & 1.4103107778075 \tabularnewline
76 & 1.42933334813494 \tabularnewline
77 & 1.45098935865143 \tabularnewline
78 & 1.48278438317301 \tabularnewline
79 & 1.56408277757764 \tabularnewline
80 & 1.56709869387710 \tabularnewline
81 & 1.57032965713959 \tabularnewline
82 & 1.59706817663672 \tabularnewline
83 & 1.60959973843666 \tabularnewline
84 & 1.66455517817392 \tabularnewline
85 & 1.67241035176915 \tabularnewline
86 & 1.81412981524401 \tabularnewline
87 & 1.87081099830136 \tabularnewline
88 & 1.98700870909012 \tabularnewline
89 & 2.15015381337444 \tabularnewline
90 & 2.46048985054225 \tabularnewline
91 & 2.46405050991360 \tabularnewline
92 & 2.4849740758858 \tabularnewline
93 & 2.62960882876486 \tabularnewline
94 & 3.05979310759203 \tabularnewline
95 & 3.10992522974607 \tabularnewline
96 & 3.82162364058846 \tabularnewline
97 & 4.69421170334864 \tabularnewline
98 & 4.78574256580058 \tabularnewline
99 & 5.29631894115553 \tabularnewline
100 & 5.59275256541108 \tabularnewline
101 & 6.62690103042577 \tabularnewline
102 & 9.27136620920313 \tabularnewline
103 & 10.035517504093 \tabularnewline
104 & 12.0429495234857 \tabularnewline
105 & 12.3153905114848 \tabularnewline
106 & 19.1206115664269 \tabularnewline
107 & 21.5471376838011 \tabularnewline
108 & 21.9887629586038 \tabularnewline
109 & 25.3853969310361 \tabularnewline
110 & 47.8250361975686 \tabularnewline
111 & 101.429906185177 \tabularnewline
112 & 110.269511702147 \tabularnewline
113 & 237.876729330625 \tabularnewline
114 & 790.268378518266 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23892&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]0.106359061673185[/C][/ROW]
[ROW][C]2[/C][C]0.130015383705161[/C][/ROW]
[ROW][C]3[/C][C]0.151103441390327[/C][/ROW]
[ROW][C]4[/C][C]0.164047432165213[/C][/ROW]
[ROW][C]5[/C][C]0.166823979091737[/C][/ROW]
[ROW][C]6[/C][C]0.194698125311981[/C][/ROW]
[ROW][C]7[/C][C]0.20057479901523[/C][/ROW]
[ROW][C]8[/C][C]0.202066919608331[/C][/ROW]
[ROW][C]9[/C][C]0.214969974647624[/C][/ROW]
[ROW][C]10[/C][C]0.221375902030912[/C][/ROW]
[ROW][C]11[/C][C]0.230470909227172[/C][/ROW]
[ROW][C]12[/C][C]0.242352140489823[/C][/ROW]
[ROW][C]13[/C][C]0.263960773600929[/C][/ROW]
[ROW][C]14[/C][C]0.266550182892457[/C][/ROW]
[ROW][C]15[/C][C]0.269730402439176[/C][/ROW]
[ROW][C]16[/C][C]0.297584021748480[/C][/ROW]
[ROW][C]17[/C][C]0.302430157226425[/C][/ROW]
[ROW][C]18[/C][C]0.321509624765963[/C][/ROW]
[ROW][C]19[/C][C]0.322617792441771[/C][/ROW]
[ROW][C]20[/C][C]0.326871243764269[/C][/ROW]
[ROW][C]21[/C][C]0.331646212099580[/C][/ROW]
[ROW][C]22[/C][C]0.333947419693491[/C][/ROW]
[ROW][C]23[/C][C]0.347556268825639[/C][/ROW]
[ROW][C]24[/C][C]0.352289667745166[/C][/ROW]
[ROW][C]25[/C][C]0.352624446117962[/C][/ROW]
[ROW][C]26[/C][C]0.361754435632208[/C][/ROW]
[ROW][C]27[/C][C]0.379893993398211[/C][/ROW]
[ROW][C]28[/C][C]0.398566820818928[/C][/ROW]
[ROW][C]29[/C][C]0.407289381153006[/C][/ROW]
[ROW][C]30[/C][C]0.414982035755767[/C][/ROW]
[ROW][C]31[/C][C]0.427641318133964[/C][/ROW]
[ROW][C]32[/C][C]0.439867356465921[/C][/ROW]
[ROW][C]33[/C][C]0.456509583689107[/C][/ROW]
[ROW][C]34[/C][C]0.462435323574999[/C][/ROW]
[ROW][C]35[/C][C]0.479006064679771[/C][/ROW]
[ROW][C]36[/C][C]0.484626464403255[/C][/ROW]
[ROW][C]37[/C][C]0.492487400854072[/C][/ROW]
[ROW][C]38[/C][C]0.51940242797056[/C][/ROW]
[ROW][C]39[/C][C]0.54748287836312[/C][/ROW]
[ROW][C]40[/C][C]0.549651531785766[/C][/ROW]
[ROW][C]41[/C][C]0.591500540997217[/C][/ROW]
[ROW][C]42[/C][C]0.603054359075532[/C][/ROW]
[ROW][C]43[/C][C]0.603082913039327[/C][/ROW]
[ROW][C]44[/C][C]0.61284294108708[/C][/ROW]
[ROW][C]45[/C][C]0.618978553660433[/C][/ROW]
[ROW][C]46[/C][C]0.624266769898895[/C][/ROW]
[ROW][C]47[/C][C]0.658144543394534[/C][/ROW]
[ROW][C]48[/C][C]0.664487399195191[/C][/ROW]
[ROW][C]49[/C][C]0.667022068600433[/C][/ROW]
[ROW][C]50[/C][C]0.669440632169874[/C][/ROW]
[ROW][C]51[/C][C]0.674934145457615[/C][/ROW]
[ROW][C]52[/C][C]0.727946999183924[/C][/ROW]
[ROW][C]53[/C][C]0.730243349936725[/C][/ROW]
[ROW][C]54[/C][C]0.730345698967277[/C][/ROW]
[ROW][C]55[/C][C]0.74675089846669[/C][/ROW]
[ROW][C]56[/C][C]0.753938352917532[/C][/ROW]
[ROW][C]57[/C][C]0.75851835060794[/C][/ROW]
[ROW][C]58[/C][C]0.783727763360603[/C][/ROW]
[ROW][C]59[/C][C]0.788209718285686[/C][/ROW]
[ROW][C]60[/C][C]0.848881711429808[/C][/ROW]
[ROW][C]61[/C][C]0.886864378884209[/C][/ROW]
[ROW][C]62[/C][C]0.887399802794659[/C][/ROW]
[ROW][C]63[/C][C]0.935656853372118[/C][/ROW]
[ROW][C]64[/C][C]0.975563492224267[/C][/ROW]
[ROW][C]65[/C][C]1.03362387951607[/C][/ROW]
[ROW][C]66[/C][C]1.09398098423581[/C][/ROW]
[ROW][C]67[/C][C]1.09607656851168[/C][/ROW]
[ROW][C]68[/C][C]1.13832573561032[/C][/ROW]
[ROW][C]69[/C][C]1.16923159514141[/C][/ROW]
[ROW][C]70[/C][C]1.24662930726834[/C][/ROW]
[ROW][C]71[/C][C]1.27195591963656[/C][/ROW]
[ROW][C]72[/C][C]1.31308665225943[/C][/ROW]
[ROW][C]73[/C][C]1.35239055059429[/C][/ROW]
[ROW][C]74[/C][C]1.36169179033375[/C][/ROW]
[ROW][C]75[/C][C]1.4103107778075[/C][/ROW]
[ROW][C]76[/C][C]1.42933334813494[/C][/ROW]
[ROW][C]77[/C][C]1.45098935865143[/C][/ROW]
[ROW][C]78[/C][C]1.48278438317301[/C][/ROW]
[ROW][C]79[/C][C]1.56408277757764[/C][/ROW]
[ROW][C]80[/C][C]1.56709869387710[/C][/ROW]
[ROW][C]81[/C][C]1.57032965713959[/C][/ROW]
[ROW][C]82[/C][C]1.59706817663672[/C][/ROW]
[ROW][C]83[/C][C]1.60959973843666[/C][/ROW]
[ROW][C]84[/C][C]1.66455517817392[/C][/ROW]
[ROW][C]85[/C][C]1.67241035176915[/C][/ROW]
[ROW][C]86[/C][C]1.81412981524401[/C][/ROW]
[ROW][C]87[/C][C]1.87081099830136[/C][/ROW]
[ROW][C]88[/C][C]1.98700870909012[/C][/ROW]
[ROW][C]89[/C][C]2.15015381337444[/C][/ROW]
[ROW][C]90[/C][C]2.46048985054225[/C][/ROW]
[ROW][C]91[/C][C]2.46405050991360[/C][/ROW]
[ROW][C]92[/C][C]2.4849740758858[/C][/ROW]
[ROW][C]93[/C][C]2.62960882876486[/C][/ROW]
[ROW][C]94[/C][C]3.05979310759203[/C][/ROW]
[ROW][C]95[/C][C]3.10992522974607[/C][/ROW]
[ROW][C]96[/C][C]3.82162364058846[/C][/ROW]
[ROW][C]97[/C][C]4.69421170334864[/C][/ROW]
[ROW][C]98[/C][C]4.78574256580058[/C][/ROW]
[ROW][C]99[/C][C]5.29631894115553[/C][/ROW]
[ROW][C]100[/C][C]5.59275256541108[/C][/ROW]
[ROW][C]101[/C][C]6.62690103042577[/C][/ROW]
[ROW][C]102[/C][C]9.27136620920313[/C][/ROW]
[ROW][C]103[/C][C]10.035517504093[/C][/ROW]
[ROW][C]104[/C][C]12.0429495234857[/C][/ROW]
[ROW][C]105[/C][C]12.3153905114848[/C][/ROW]
[ROW][C]106[/C][C]19.1206115664269[/C][/ROW]
[ROW][C]107[/C][C]21.5471376838011[/C][/ROW]
[ROW][C]108[/C][C]21.9887629586038[/C][/ROW]
[ROW][C]109[/C][C]25.3853969310361[/C][/ROW]
[ROW][C]110[/C][C]47.8250361975686[/C][/ROW]
[ROW][C]111[/C][C]101.429906185177[/C][/ROW]
[ROW][C]112[/C][C]110.269511702147[/C][/ROW]
[ROW][C]113[/C][C]237.876729330625[/C][/ROW]
[ROW][C]114[/C][C]790.268378518266[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23892&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23892&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of Dendrogram
LabelHeight
10.106359061673185
20.130015383705161
30.151103441390327
40.164047432165213
50.166823979091737
60.194698125311981
70.20057479901523
80.202066919608331
90.214969974647624
100.221375902030912
110.230470909227172
120.242352140489823
130.263960773600929
140.266550182892457
150.269730402439176
160.297584021748480
170.302430157226425
180.321509624765963
190.322617792441771
200.326871243764269
210.331646212099580
220.333947419693491
230.347556268825639
240.352289667745166
250.352624446117962
260.361754435632208
270.379893993398211
280.398566820818928
290.407289381153006
300.414982035755767
310.427641318133964
320.439867356465921
330.456509583689107
340.462435323574999
350.479006064679771
360.484626464403255
370.492487400854072
380.51940242797056
390.54748287836312
400.549651531785766
410.591500540997217
420.603054359075532
430.603082913039327
440.61284294108708
450.618978553660433
460.624266769898895
470.658144543394534
480.664487399195191
490.667022068600433
500.669440632169874
510.674934145457615
520.727946999183924
530.730243349936725
540.730345698967277
550.74675089846669
560.753938352917532
570.75851835060794
580.783727763360603
590.788209718285686
600.848881711429808
610.886864378884209
620.887399802794659
630.935656853372118
640.975563492224267
651.03362387951607
661.09398098423581
671.09607656851168
681.13832573561032
691.16923159514141
701.24662930726834
711.27195591963656
721.31308665225943
731.35239055059429
741.36169179033375
751.4103107778075
761.42933334813494
771.45098935865143
781.48278438317301
791.56408277757764
801.56709869387710
811.57032965713959
821.59706817663672
831.60959973843666
841.66455517817392
851.67241035176915
861.81412981524401
871.87081099830136
881.98700870909012
892.15015381337444
902.46048985054225
912.46405050991360
922.4849740758858
932.62960882876486
943.05979310759203
953.10992522974607
963.82162364058846
974.69421170334864
984.78574256580058
995.29631894115553
1005.59275256541108
1016.62690103042577
1029.27136620920313
10310.035517504093
10412.0429495234857
10512.3153905114848
10619.1206115664269
10721.5471376838011
10821.9887629586038
10925.3853969310361
11047.8250361975686
111101.429906185177
112110.269511702147
113237.876729330625
114790.268378518266


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = ward ; par2 = ALL ; par3 = FALSE ; par4 = FALSE ;
Parameters (R input):
par1 = ward ; par2 = ALL ; par3 = FALSE ; par4 = FALSE ;
R code (references can be found in the software module):
par3 <- as.logical(par3)
par4 <- as.logical(par4)
if (par3 == 'TRUE'){
dum = xlab
xlab = ylab
ylab = dum
}
x <- t(y)
hc <- hclust(dist(x),method=par1)
d <- as.dendrogram(hc)
str(d)
mysub <- paste('Method: ',par1)
bitmap(file='test1.png')
if (par4 == 'TRUE'){
plot(d,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8),type='t',center=T, sub=mysub)
} else {
plot(d,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8), sub=mysub)
}
dev.off()
if (par2 != 'ALL'){
if (par3 == 'TRUE'){
ylab = 'cluster'
} else {
xlab = 'cluster'
}
par2 <- as.numeric(par2)
memb <- cutree(hc, k = par2)
cent <- NULL
for(k in 1:par2){
cent <- rbind(cent, colMeans(x[memb == k, , drop = FALSE]))
}
hc1 <- hclust(dist(cent),method=par1, members = table(memb))
de <- as.dendrogram(hc1)
bitmap(file='test2.png')
if (par4 == 'TRUE'){
plot(de,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8),type='t',center=T, sub=mysub)
} else {
plot(de,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8), sub=mysub)
}
dev.off()
str(de)
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of Dendrogram',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Label',header=TRUE)
a<-table.element(a,'Height',header=TRUE)
a<-table.row.end(a)
num <- length(x[,1])-1
for (i in 1:num)
{
a<-table.row.start(a)
a<-table.element(a,hc$labels[i])
a<-table.element(a,hc$height[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
if (par2 != 'ALL'){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of Cut Dendrogram',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Label',header=TRUE)
a<-table.element(a,'Height',header=TRUE)
a<-table.row.end(a)
num <- par2-1
for (i in 1:num)
{
a<-table.row.start(a)
a<-table.element(a,i)
a<-table.element(a,hc1$height[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}