Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*Unverified author*

R Software Module

rwasp_agglomerativehierarchicalclustering.wasp

Title produced by software

Agglomerative Nesting (Hierarchical Clustering)

Date of computation

Fri, 29 Jan 2010 10:58:31 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Jan/29/t1264788670r9j3ccuopjdbvmj.htm/, Retrieved Thu, 02 May 2024 05:49:26 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=72734, Retrieved Thu, 02 May 2024 05:49:26 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

These contain a cluster analysis of the subjective reactions of 111 judges to 8 female speakers: 1 and 2 Chinese Americans, 3 and 4 Korean Americans, 5 and 6 European Americans, 7 African American, 8 Latino. Reaction categories include: intelligent, slacker, fun, loner, strong personality, studious. Clusters map perceived race but not actual race.

IsPrivate?

No (this computation is public)

User-defined keywords

Subjective Reaction Tests, perceptual dialectology, Asian Americans, African Americans, European Americans, Latinos.

Estimated Impact

209

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Agglomerative Nesting (Hierarchical Clustering)] [Subjective Reacti...] [2010-01-29 17:58:31] [d41d8cd98f00b204e9800998ecf8427e] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

2	3	3	4	3	1	3	3	2	3	2	3	3	3	2	2	2	2	3	2	3	3	4	3	4	1	3	3	3	1	3	3	2	2	2	3	4	4	1	2	1	4	3	3	3	4	2	3	2	3	2	2	1	3	2	2	3	3	2	3	3	2	3	2	2	2	1	2	2	3	2	2	3	2	3	2	1	3	3	3	3	3	3	3	3	3	3	2	2	3	2	3	3	3	2	2	2	2	1	3	1	1	2	4	1	3	1	4	3	2	2	3	1	2	1	2	3	3	2	3	3	2	2	1	2	1	2	3	3	2	2	2	1	2	3	1	3	3	1	2	3	2	2	2	2	3	1	1	4	2	3	3	1	3	2	2	1	2	2	3	2	2	2	4	3	3	3	2	1	2	2	2	1	3	2	3	3	2	2	2	2	3	3	3	3	2	3	4	2	1	2	2	1	2	2	1	2	1	3	3	3	2	1	1	2	2	3	2	2	3	3	3	4	3	1	2	1	4	2	3	2	2	3	3	2	4	4	2	3	2	2	2	3	3	3	4	3	3	3	3	3	2	2	2	3	2	2	3	3	1	3	2	3	3	3	4	2	2	4	4	2	3	1	3	2	3	3	4	2	3	1	3	2	3	3	3	2	4	4	3	1	3	3	3	2	3	3	2	1	2	3	3	2	2	2	3	3	2	2	3	3	3	2	3	3	4	3	4	3	2	2	2	3	2	3	3	3	2	3	3	2	3	1	2	3	4	1	2	3	3	2	2	2	1	1	1	1	2	3	3	2	2	2	1	2	2	1	1	2	2	2	2	2	2	3	3	2	1	2	1	1	2	3	2	2	2	1	2	1	1	3	3	2	2	1	2	1	1	1	2	2	2	2	2	2	1	2	2	2	2	2	2	2	2	1	3	1	4	4	1	2	2	2	2	2	3	2	2	2	2	1	1	2	2	1	1	2	1	1	2	2	2	3	1	1	2	2	2	3	3	1	1	1	2	1	1	4	3	1	1	1	2	3	2	2	3	3	4	3	2	3	3	2	2	3	3	3	4	2	3	3	4	4	2	2	1	2	2	2	2	3	1	3	2	2	3	2	2	2	3	3	1	3	2	2	3	3	2	3	3	3	2	3	3	2	2	1	3	2	3	4	3	2.609090909	3	2	3	3	3	2	4	2	2	2	3	2	4	4	2	3	3	3	1	3	3	2	3	3	3	3	4	3	3	2	2	3	2	3	3	2	2	2	3	3	4	1	4	3	1	2	2	3	3	3	2	3	2	2	3	3	3	1	3	2	2	2.386138614	2	3	3	3	2	3	2	2	3	4	2	4	4	2	4	1	1	1	3	2	3	3	3	3	2	2	3	1	3	1	2	3	3	4	2	3	2	3	2	3	2	2	1	2	2	1	4	3	2	3	3	2	2	2	2	3	1	3	2	3	2	2	2	2	3	2	1	3	3	3	2	3	3	2	3	2	3	3	2	2	2	4	3	3	2	2	2	2	2	3	1	1	3	1	1	3	1	3	3	2	2
3	3	2	3	4	3	3	3	3	3	3	3	3	3	2	3	3	3	3	4	3	3	3	2	3	2	4	3	2	3	3	3	2	3	2	4	4	4	3	2	3	1	3	2	4	3	2	2	2	3	3	2	2	3	4	3	3	3	2.690909091	3	2	2	1	2	2	4	2	3	3	2	2	2	3	2	3	3	3	2	3	3	3	3	3	2	2	4	3	3	2	2	1	2	2	3	2	2	3	3	3	2	2	3	2	4	3	2	2	2	3	2	3	1	2	3	1	1	3	3	2	3	3	1	2	2	2	3	1	2	2	2	1	2	3	2	2	1	3	1	1	3	2	3	2	3	1	3	1	2	4	2	2	2	2	2	3	2	3	2	2	2	2	2	3	1	2	1	2	2	1	2.172727273	2	3	1	2	3	3	1	3	2	2	2	3	3	3	2	2	2	2	3	2	2	3	1	2	1	3	2	2	2	4	3	4	3	3	2	2	3	2	2	1	2	3	2	3	1	3	1	3	3	2	2	2	1	3	3	1	2	3	3	2	3	2	2	2	2	3	2	2	2	3	3	3	2	2	3	2	1	2	3	1	2	2	1	3	1	4	3	4	3	4	3	3	2	1	2	2	3	1	2	2	3	3	3	2	2	2	3	2	2	3	2.281818182	3	2	4	2	2	3	4	1	2	3	2	2	1	2	2	3	3	1	2	2	2	2	3	3	2	3	2	2	3	3	3	2	4	3	2	2	2	1	2	3	1	1	2	2	1	2	2	1	2	2	2	2	3	2	1	4	4	3	3	3	2	2	2	3	2.209090909	1	3	3	3	2	3	2	2	1	3	2	1	2	1	1	3	2	2	2	3	1	2	1	2	4	1	2	2	2	2	3	1	3	2	3	2	2	2	3	2	2	2	2	2	2	2	2	2	1	1	3	2	1	1	1	2	2	2	4	4	1	2	2	2	3	3	3	2	2	1	2	2	3	1	2	3	3	4	1	1	2	2	3	3	3	2	3	3	1	2	4	2	1	2	3	2	2	4	2	2	1	1	1	3	3	3	3	2	1	1	3	3	1	3	2	2	3	3	2	2	3	3	2	2	3	1	2	3	2	3	1	3	3	4	3	4	3	2	3	1	2	2	3	1	2	2	2	3	3	2	2	2	3	2	3	1	2	2	2	3	2	1	2	3	2	2	3	2	3	1	2	2	3	3	1	2	2	3	2	2	3	2	3	2	2	2	2	2	1	2	3	2	2	2	1	2	3	1	2	2	2	4	2	3	2	1	3	2	2	3	2	1	4	4	2	3	2	3	3	4	3	3	3	3	3	2	3	2	4	2	2	3	2	3	2	3	3	3	3	3	3	3	3	3	4	4	4	3	2	3	2	3	2	3	3	2	2	2	3	2	2	2	3	2	3	3	3	3	2	3	2	2	2	3	4	3	3	3	2	2	3	3	3	3	4	3	2	3	3	3	3	2	4	2	4	3	3	4	2	1	4	3	3	2.718181818	3	3	2	4	2	2	2	2	1	2	2	2	2	3	3	2
3	3	2	3	4	2	3	2	4	3	4	2	4	4	1	3	2	3	3	3	3	3	1	2	4	3	3	3	3	2	4	3	3	2	3	3	4	4	2	3	3	3	3	3	4	4	2	3	4	3	3	3	3	2	3	2	2	3	3	3	2	2	2	1	2	4	2	2	3	2	4	1	3	2	4	3	2	3	3	4	1	3	3	4	3	2	3	2	3	2	1	3	2	3	3	3	2	3	2	3	3	3	3	4	3	4	3	4	2	2	3	2	2	2	2	1	3	3	2	1	2	2	2	3	1	2	1	3	2	3	2	2	1	1	3	1	2	2	1	2	3	1	2	2	3	3	1	1	3	4	1	1	1	2	2	1	1	2	2	2	2	1	2	2	2	2	3	3	1	2	1	2	2	2	3	2	1	4	2	3	3	1	2	3	3	2	2	4	2	2	1	3	1	2	1	2	2	2	1	2	3	3	2	3	2	2	2	2	1	3	2	2	3	3	1	2	1	1	2	3	3	1	1	3	2	1	4	2	3	2	3	2	3	2	3	3	2	3	3	1	3	3	2	3	2	2	1	1	2	1	3	2	1	3	2	2	2	1	2	4	1	3	1	1	3	2	4	2	2	2	1	2	3	2	3	2	2	3	1	3	1	3	1	2	1	1	3	3	2	2	2	2	2	1	2	2	3	3	1	1	1	1	2	2	3	2	1	2	3	4	2	2	1	3	2	3	2	2	1	2	3	2	1	2	3	1	3	1	2	3	2	2	1	4	3	3	4	4	3	3	3	1	2	3	2	2	3	3	2	2	4	3	2	3	3	2	3	1	4	1	1	2	3	3	2	2	3	3	2	3	4	4	2	3	1	2	3	1	2	2	3	4	3	1	3	2	3	3	3	4	1	3	2	3	3	2	2	2	1	4	3	3	3	3	4	4	3	2	2	4	4	3	4	3	3	1	3	4	2	4	4	4	3	2	2	1	2	3	2	4	1	2	3	2	1	3	1	2	1	4	3	3	3	3	1	2	3	1	2	2	3	2	3	2	1	2	3	2	1	2	3	1	2	3	1	1	2	2	1	1	3	1	3	2	2	3	2	1	1	2	1	4	1.754545455	3	2	2	2	1	3	1	2	2	1	1	2	2	3	2	2	2	2	1	2	2	1	1	1	2	2	1	1	1	2	1	2	1	1	2	3	2	1	1	1	1	1	1	2	2	1	1	1	2	1	2	1	1	3	3	2	2	1	2	2	1	1	1	2	4	3	1	1	1	2	2	1	2	3	2	4	4	2	3	3	4	3	3	3	2	4	1	3	3	3	3	3	3	3	1	3	3	4	3	3	3	2	4	3	3	3	2	3	3	4	2	4	3	4	3	3	4	3	2	3	4	3	2	3	2	3	2	2	4	4	3	3	3	2	2	2	3	3	2	2	3	2	4	1	3	3	4	3	1	3	3	3	1	3	3	3	3	1	4	2	3	3	2	3	2	2	3	2	3	3	2	3	4	1	2	4	3	3	3	4	3	2	4
4	3	3	2	2	2	3	2.736363636	4	3	1	3	4	4	4	2	2	2	4	3	3	2	3	3	4	2	3	3	3	2	3	3	2	4	3	3	4	4	4	2	2	3	3	3	3	4	3	3	4	3	3	2	3	3	4	2	3	3	3	3	2	2	2	3	2	3	1	3	3	3	4	2	3	3	3	3	2	2	3	2	1	3	3	3	3	2	2	2	2	3	3	2	4	3	2	3	1	3	3	2	2	2	3	1	3	3	2	3	2	2	2	2	1	2	2	1	2	3	2	1	2	3	1	1	3	1	2	3	3	2	2	2	1	1	2	1	1	3	1	2	3	2	2	3	1	1	1	1	4	1	2	2	1	3	2	1	1	2	2	2	2	2	3	2	2	1	3	1	1	1	2	1	1	3	3	3	1	3	1	2	2	1	2	2	2	2	2	3	3	1	3	2	1	2	3	1	3	2	1	3	2	1	3	1	2	2	2	3	1	2	1	3	2	2	4	2	1	3	1	3	3	2	3	3	2	2	4	3	3	3	3	2	4	2	3	3	1	3	3	2	3	3	2	3	3	2	1	3	3	1	3	2	3	3	2	3	2	2	3	4	3	3	1	3	3	3	3	3	2	3	2	3	2	3	3	3	3	3	3	3	1	3	2	3	2	1	2	3	1	2	2	2	2	2	2	2	3	3	3	2	3	2	2	3	3	3	4	4	3	4	2	3	2	2	3	3	2	2	2	3	3	3	3	2	2	1	1	2	3	3	2	2	2	3	1	1	2	1	2	3	2	2	2	2	2	2	2	3	2	2	2	2	2	2	1	4	2	1	3	1	1	2	3	1	2	3	3	3	2	1	4	1	2	2	1	2	2	1	4	2	2	2	2	2	2	2	2	2	1	2	1	2.1	2	2	1	1	3	2	1	3	2	3	2	3	3	3	2	2	2	2	2	2	2	3	2	1	3	1	2	2	2	4	2	2	2	2	2	3	2	2	1	2	4	2	1	2	4	3	1	3	2	3	2	3	1	3	2	2	4	2	3	2	3	2	2	2	3	2	2	3	2	3	3	3	3	1	3	2	3	2	2	1	3	1	3	3	2	1	1	3	2	4	4	3	1	2	3	2	3	1	2	2	3	2	2	2	2	3	2	2	2	2	1	2	3	1	2	1	2	3	2	2	2	2	2	1	3	2	3	3	2	2	3	2	2	2	3	3	2	4	3	3	1	2	3	3	3	2	2	3	2	2	3	1	2	1	3	1	2	3	2	1	3	2	1	2	3	1	2	1	3	2	3	4	3	1	3	4	3	4	3	3	2	3	3	3	3	3	3	4	3	1	3	3	2	3	3	2	4	3	3	4	4	4	3	3	3	4	3	4	4	3	3	4	3	3	2	2	3	4	1	4	4	3	3	4	1	3	3	3	4	1	3	3	3	4	3	3	3	3	3	2	2	4	3	2	3	2	3	3	2	4	2	2	2	4	4	3	3	3	3	1	3	2	3	2	1	3	1	2	3	1	4	3	2	1
4	3	4	4	4	3	3	3	2	3	4	3	3	3	3	3	3	3	3	3	3	4	3	3	4	3	4	3	3	4	4	2	2	4	4	4	4	3	4	3	3	3	3	2	4	3	3	3	3	3	3	3	2	3	4	4	3	4	2	3	3	3	1	3	3	4	4	3	3	4	3	4	3	4	4	3	3	4	3	4	3	3	4	2	4	4	3	1	4	3	3	3	3	3	3	2	3	4	3	3	3	2	2	4	3	3	3	3	3	3	3	1	1	1	1	1	2	3	2	3	2	1	2	1	1	1	1	1	3	2	2	2	1	2	2	1	2	2	1	1	1	1	2	1	1	1	1	1	3	1	2	2	1	2	3	1	1	2	2	1.581818182	2	2	2	3	2	1	1	1	1	2	1	1	1	1	1	3	1	1	1	2	1	2	1	2	1	2	2	1	1	2	1	2	1	1	2	1	1	2	2	1	2	2	2	2	2	2	2	2	1	1	2	1	3	2	1	2	1	2	2	2	2	2	2	3	1	1	4	3	3	3	3	2	3	3	4	4	3	3	3	2	3	3	3	3	3	2	1	3	3	1	3	3	3	2.827272727	2	3	3	4	3	3	3	3	3	3	2	2	3	3	2	3	3	3	3	3	2	2	3	3	3	3	2	4	3	3	2	1	2	4	3	3	2	2	2	4	3	3	3	3	2	2	3	4	2	3	3	2	4	4	3	3	3	3	3	4	3	3	3	3	3	3	3	3	4	3	3	1	3	3	4	3	3	3	3	4	1	1	1	2	2	3	2	2	2	1	2	2	1	1	2	2	3	2	2	2	1	3	1	1	1	1	1	1	1	1	2	3	1	2	1	1	3	1	2	1	1	2	2	1	1	2	2	2	2	2	2	2	2	2	1	2	1	2	1	2	1	3	3	2	1	2	1	3	2	2	1	3	1	2	2	1	2	1	1	3	1	1	2	1	1	2	2	2	2	2	1	1	2	2	3	2	2	1.718181818	1	3	1	2	1	1	1	2	2	2	2	2	1	3	4	3	3	3	3	4	3	3	4	2	3	3	3	2	3	2	4	3	3	3	3	3	3	3	3	1	3	3	4	3	2	3	3	4	2	3	3	3	3	3	3	3	4	3	2	3	3	3	3	3	2	3	3	3	3	4	3	4	4	3	1	1	4	3	4	4	2	3	2	4	2	3	4	3	2	2	3	4	2	3	3	2	3	4	3	3	4	3	3	4	3	2	3	2	3	3	3	2	3	2	2	4	3	3	3	2	3	2	2	3	3	2	4	3	2	3	4	2	3	1	3	2	3	3	3	3	2	3	3	3	4	3	2	4	3	3	3	3	4	4	3	3	4	4	4	3	2	4	3	3	2	3	2	4	3	3	3	2	3	3	3	2	3	4	4	3	4	4	3	3	3	2	3	3	4	4	3	3	3	3	2	3	3	4	3	3	4	3	4	3	2	3	3	3	3	3	1	3	3	3	4	3	3	3	3	2	3	3	3	4	2	3	1	3	3	4	3	3	3	2
4	3	3	4	2	4	3	3	3	4	2	3	2	4	4	3	2	2	4	4	4	4	4	3	2	3	4	3	3	3	3	3	3	4	4	3	4	1	3	2	3	3	4	3	4	4	2	4	3	3	4	3	3	2	3	2	4	4	4	2	3	2	2	2	3	4	3.227272727	4	3	3	4	4	4	4	3	3	4	4	4	4	3	4	4	3	3	4	3	3	4	3	3	3	3	4	3	3	3	3	3	4	3	3	4	4	2	4	2	4	3	3	3	1	1	2	1	1	2	3	2	2	2	2	2	1	1	1	1	3	2	1	1	1	1	2	3	2	2	1	1	2	1	2	2	2	1	1	1	1	1	2	2	1	1	1	2	1	1	2	2	1	2	1	3	2	3	3	3	1	1	2	2	2	1	3	2	2	1	1	1	2	2	1	1	1	1	2	2	1	1	1	1	2	1	1	1	1	1	2	1	1	2	2	1	1	1	1	2	2	1	3	1	2	1	1	1	2	1	2	2	2	1	1	3	3	2.651376147	1	3	3	3	3	1	2	2	3	3	4	3	1	2	4	4	3	3	4	3	3	2	2	2	1	2.651376147	3	2	3	3	3	3	3	4	1	2	3	1	1	1	2	3	2	2	3	3	2	2	2	2	2	3	3	4	3	3	4	3	4	1	2	2	4	4	2	2	4	4	1	3	3	3	1	3	3	4	3	2	4	3	3	3	3	3	3	2	3	3	3	3	2	3	2	3	4	2	3	1	3	3	1	2	2	4	3	2	3	3	4	3	2	3	3	2	3	3	2	3	2	3	3	4	3	4	3	2	3	4	4	3	3	2	3	3	3	3	3	4	3	3	3	4	4	3	4	1	3	3	3	4	3	3	3	3	3	3	4	3	4	2	3	2	2	2	4	4	3	2	3	3	3	2	2	4	3.081818182	4	3	3	4	4	4	3	3	3	4	4	4	4	4	4	4	3	3	4	3	2	3	3	3	4	3	3	2	2	3	3	2	3	3	2	4	4	3	3	2	3	3	2	4	4	4	2.834862385	4	4	3	3	2.834862385	2	2	1	3	4	4	3	3	2	1	4	4	2	1	2	2	3	3	3	1	3	3	2	3	3	3	4	3	3	1	4	2	2	2	3	4	2	3	3	3	2	3	3	3	3	1	2	2	4	3	3	2	4	3	2	2	3	3	4	3	2	3	4	4	4	4	3	2	4	2	4	4	3	4	4	3	4	3	3	4	2	2	3	4	3	1	2	2	2	3	1	2	3	3	3	1	3	4	3	2	3	3	3	4	3	2	3	3	2	3	3	2	3	2	3	3	4	3	4	3	2	3	4	4	3	3	2	3	3	3	3	3	4	3	3	3	4	4	3	4	1	3	3	3	4	3	3	3	3	3	3	4	3	4	2	3	2	2	2	4	4	3	2	3	3	3	2	2	4	3.081818182	4	3	3	4	4	4	3	3	3	4	4	4	4	4	4	4	3	3	4	3	2	3	3	3	4	3	3	2	2	3	3	2	3	3	2	4	4	3	3	2	3	3	2	4
3	2	4	2	3	3	3	2	1	3	1	2	3	3	1	2	2	3	4	3	2	4	2	3	3	2	4	3	3	2	4	3	2	2	2	2	3	4	4	2	2	2	3	3	3	4	2	3	1	3	2	3	1	3	2	3	2	3	2	2	3	2	3	2	2	3	2	3	2	1	1	3	2	2	4	2	2	3	2	3	3	2	3	3	3	1	3	1	1	3	2.427272727	2	2	3	2	1	2	3	3	2	2	1	2	4	2	1	2	2	3	2	1	3	3	2	4	3	2	2	3	3	2	4	3	3	3	4	1	3	2	1	2	3	1	2	3	1	3	2	1	2	3	2	2	3	3	3	3	4	4	3	3	3	1	3	2	3	1	2	3	4	3	1	2	4	2	3	2	3	1	3	2	3	3	3	3	4	1	3	1	2	3	4	2	3	2	2	3	3	3	3	1	2	3	3	2	3	3	3	3	4	2	3	3	3	2	2	3	2	2	3	3	2	4	3	1	3	3	2	3	2	3	3	1	3	3	4	4	3	3	3	2	2	4	3	3	2	1	3	3	2	3	3	3	3	4	2	2	4	2	1	3	2	3	3	3	4	3	3	2	4	3	2	1	1	3	4	4	3	2	3	1	3	3	3	3	2	2	4	3	2	2.554545455	3	3	2	2	2	3	3	2	2	3	2	1	3	2	2	3	3	1	2	2	2	1	1	2	2	3	4	3	2	2	3	3	3	3	3	2	2	3	2	3	2	3	1	3	1	2	3	2	4	3	2	2	1	2	2	1	1	2	3	2	1	2	1	1	2	2	2	1	3	3	1	2	2	3	2	2	1	1	1	1	2	3	2	2	2	1	3	1	2	4	2	2	1	2	2	1	1	1	2	2	1	2	1	3	2	2	2	2	1	1	2	2	2	3	3	3	1	1	2	1	2	2	2	2	2	1.818181818	2	2	2	2	2	2	2	1	2	3	2	1	1	1	1	2	2	1	1	2	2	2	1	2	2	2	1	1	2	4	2	3	1	1	2	2	3	3	3	1	4	4	3	3	3	2	2	4	4	3	3	1	3	3	4	4	3	3	2	4	4	1	3	2	1	3	2	4	3	3	4	3	1	2	4	4	3	4	1	3	4	4	4	3	3	4	3	3	4	2	3	3	3	4	4	4	2	4	4	3	3	3	4	4	3	2	1	2	3	3	1	4	3	1	3	1	2	2	2	3	2	2	4	4	3	4	4	1	4	3	3	2	3	4	3	2	4	4	1	3	4	3	2	2	3	4	3	4	1	2	1	1	2	3	3	3	2	3	1	2	3	2	1	2	3	2	3	2	2	3	4	2	1	2	3	3	3	2	3	3	3	3	3	1	2	4	3	2	2	2	3	2	2	3	2	2	1	3	2	3	3	2	2	3	2	4	2	2	2	2	2	2	1	3	2	3	1	1	1	3	3	1	4	2	1	2	1	2	4	1	2	2	2	2	2	1	1	2	2	3	2	3	2	2	2	3	2	2	2	1	2	1	1	1	2	2	2	2	2
2	3	4	4	4	3	3	3	2	3	1	2	2	3	1	3	2	3	4	3	4	4	3	2	3	1	4	3	3	2	4	3	2	2	3	1	4	3	4	2	3	2	3	3	4	3	2	3	3	3	2	3	2	2	2	3	2	3	3	3	1	3	1	3	3	3	3	2	2	3	1	2	1	3	4	3	3	4	2	3	1	2	3	2	3	4	2	3	2	3	3	4	3	3	2	2	4	3	2	2	2.7	1	3	4	3	3	4	3	2	2	3	2	3	4	1	1	2	3	2	2	2	2.091743119	2	3	2	3	1	2	2	1	2	1	1	3	3	1	3	2	1	2	3	2	2	3	1	1	3	1	3	2	2	2	2	2	1	1	1	2	2	1	2	1	2	3	3	3	2	4	1	1	2	3	2	3	2	3	1	1	2	2	2	3	3	4	1	2	3	1	2	2	2	3	1	1	2	1	1	3	2	3	3	3	1	2	2	3	2	2	1	3	2	2.091743119	4	3	4	2	1	1	2	3	3	2	2	3	3	4	4	3	3	3	3	2	3	3	3	3	2	2	3	2	4	3	3	4	3	3	3	2	3	1	2	2	3	3	2	3	2	1	2	3	4	3	1	2	2.614678899	3	4	1	3	3	3	3	3	2	3	3	2	3	2	3	2.614678899	3	2	3	2	2	4	2	4	2	3	2	1	2	2	3	3	3	4	3	3	4	2	1	3	3	2	2	2	1	3	2	2	2	3	3	2	2	3	2	3	3	4	1	3	1	3	2	4	3	3	2	2	1	1	1	1	2	1	3	1	2	2	2	1	2	1	2	2	3	2	2	2	2	1	2	1	1	2	1	1	2	2	2	2	3	1	2	3	1	3	1	2	1	1	2	1	1	2	2	2	1	2	1	3	2	2	3	2	2	1	2	1	2	1	4	3	2	1	1	2	2	3	3	2	3	1	2	2	1	2	2	1	2	1	1	2	1	3	2	4	2	3	2	3	2	2	2	2	2	2	3	1	2	1	2	4	2	1	1	2	2	2	2	3	3	3	4	4	3	3	4	3	2	3	4	3	4	1	3	2	3	4	3	3	3	3	2	4	2	2	1	2	3	4	3	2	3	3	1	2	1	4	3	3	1	3	4	4	1	2	3	2.718181818	4	3	3	2	3	2	2	2	1	3	2	3	2	2	3	1	1	3	2	3	3	2	4	1	4	4	3	4	2	3	4	1	3	4	4	3	1	3	1	3	2	4	4	4	3	2	2	3	2	1	4	4	2	3	1	2	3	4	3	3	2	3	1	2	1	4	4	3	3	3	3	3	3	2	3	3	1	3	2	3	3	2	3	3	3	2	3	1	3	3	3	2	3	3	3	3	3	1	3	1	3	2	3	2	3	3	3	3	2	3	3	3	2	3	2	2	2	2	1	3	3	3	2	3	3	2	2	3	4	2	2	2	1	3	1	4	4	3	3	3	3	3	1	1	3	2	3	4	2	4	2	2	4	4	3	3	2	2	3	3	2	2	2	1	3	1	2	3	4	3	3	2	3

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	9 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\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 & 9 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72734&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=72734&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72734&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	9 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Agglomerative Nesting (Hierarchical Clustering)
Agglomerative Coefficient	0.215128069345944

\begin{tabular}{lllllllll}
\hline
Agglomerative Nesting (Hierarchical Clustering) \tabularnewline
Agglomerative Coefficient & 0.215128069345944 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72734&T=1

[TABLE]
[ROW][C]Agglomerative Nesting (Hierarchical Clustering)[/C][/ROW]
[ROW][C]Agglomerative Coefficient[/C][C]0.215128069345944[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=72734&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72734&T=1

As an alternative you can also use a QR Code:

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

Agglomerative Nesting (Hierarchical Clustering)
Agglomerative Coefficient	0.215128069345944

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = euclidean ; par2 = ward ; par3 = 1 ; par4 = 0.5 ; par5 = 0.5 ; par6 = 0.5 ; par7 = 0 ;

Parameters (R input):

par1 = euclidean ; par2 = ward ; par3 = 1 ; par4 = 0.5 ; par5 = 0.5 ; par6 = 0.5 ; par7 = 0 ;

R code (references can be found in the software module):

par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
par6 <- as.numeric(par6)
par7 <- as.numeric(par7)
library(cluster)
if (par2 == 'flexible')
{
if (par3 == 1) pm <- c(par4)
if (par3 == 3) pm <- c(par4,par5,par6)
if (par3 == 4) pm <- c(par4,par5,par6,par7)
ag <- agnes(t(y),metric=par1,method=par2,par.method=pm)
} else {
ag <- agnes(t(y),metric=par1,method=par2)
}
mysub <- paste('Method: ',par2)
summary(ag)
bitmap(file='test1.png')
plot(ag,which.plots=2,main=main,sub=mysub,xlab=xlab,ylab=ylab)
dev.off()
bitmap(file='test2.png')
plot(ag,which.plots=1,main='Banner',sub=mysub,xlab=ylab,ylab=xlab)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Agglomerative Nesting (Hierarchical Clustering)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Agglomerative Coefficient',header=TRUE)
a<-table.element(a,ag$ac)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code