Multidimensional scaling cluster analysis
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Multidimensional Scaling & Cluster Analysis. STAT 3611 Zeyun Lin & Hong Liu 4/16/2013. Data Explanation . The data we selected is from “2012 County Health Ranking Minnesota Data”

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Multidimensional Scaling & Cluster Analysis

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Multidimensional scaling cluster analysis

Multidimensional Scaling & Cluster Analysis

STAT 3611

Zeyun Lin & Hong Liu

4/16/2013


Data explanation

Data Explanation

  • The data we selected is from “2012 County Health Ranking Minnesota Data”

  • We carried out both Multidimensional Scaling (Classical) and Cluster Analysis (Agglomerative Hierarchical Clustering---Complete Linkage method)

  • There are 6 variables (“Mortality”, “Morbidity”, “Health Behaviors”, “Clinical Care”, “Social Economic” and “Physical Environment”) and 84 counties in the data, but both MDS and Cluster Analysis are shown the relationship among these 84 cases, not the 6 variables.


Method 1 multidimensional scaling

Method 1: Multidimensional Scaling

Cook

Steven


Method 2 cluster analysis

Method 2: Cluster Analysis


Combine mds cluster analysis

Combine MDS & Cluster analysis

A

C

B

C

B

A

D

D


Interpretation

Interpretation

  • Combine MDS with Cluster Analysis

    • In MDS, Steven and Cook are close to each other, which means they behave similarly

    • In Cluster Analysis, we observed the same pattern

    • The other two clusters highlighted in both graphs are illustrated the same clustering pattern

  • Reason of chosen Complete linkage method

    • Complete linkage tends to find compact clusters of approximately equal diameters.

    • Complete method avoids a drawback of single linkage which is chaining phenomenon, where clusters formed via single method may be forced together due to single elements being close to each other


Questions or comments

Questions or Comments ?

Thank you for your time!!


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