08_Chapter 09(1) - Click to edit Master subtitle style Ch 1...

Info iconThis preview shows pages 1–21. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Click to edit Master subtitle style Ch 1 9. Cluster Analysis 11 Ch 1 Decision Pr ocess 1. Research Objective 2. Research Design 3. Assumption Test 4. Estimating the Cluster Analysis Model and Assessing Overall Fit 5. Interpretation 6. Validation 22 Ch 1 1. Resear ch Objective Factor Analysis vs. Cluster Analysis Factor analysis Categorize variables into factors Loadings Cluster analysis Categorize respondents into clusters/segments Responses 33 Ch 1 1. Resear ch Objective An example Whole Foods is interested in segmenting consumers into categories according to their attitudes toward organic foods. 44 ID X1 (I love organic foods: 1-5) 1 2 3 4 5 6 7 8 9 10 5 3 2 5 3 2 2 5 2 3 One Var iable Cluster ID X1 1 2 3 4 5 6 7 8 9 10 5 3 2 5 3 2 2 5 2 3 Cluster 1 Cluster 2 Cluster 3 One Var iable Cluster ID X1 Cluster 1 2 3 4 5 6 7 8 9 10 5 3 2 5 3 2 2 5 2 3 1 2 3 1 2 3 3 1 3 2 One Var iable Cluster X1 (I love marketing: 1 - 10) X2 (I love accounting: 1-10) A B C D E 2 3 7 8 2 6 9 1 3 2 T wo Var iable Cluster Ch 1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 A B C D E L ow H igh L ow High M a rke tin g (X1 ) A c c o u n t i n g ( X 2 ) Ch 1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 A B C D E Low High Low H igh M arketing (X1) A c c o u n t i n g ( X 2 ) X1 (Markeing:1 - 10) X2 (Accounting: 1-10) A B C D E 2 3 7 8 2 6 9 1 3 2 Euclidean Distance AB AC AD AE BD BE CD CE DE 162 . 3 ) 9 6 ( ) 3 2 ( ) ( ) ( 2 2 2 2B 2A 2 1B 1A =- +- =- +- = x x x x d AB Ch 1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 A B C D E Low Hig h Low Hig h 3.162 Mar ketin g (X1) A c c o u n t i n g ( X 2 ) Euclidean Distance AB AC AD AE BC BD BE CD CE DE 3.162 7.071 6.708 4.000 8.944 7.810 7.071 2.236 5.099 6.083 Same cluster: Shortest distance between two respondents Euclidean Distance AB AC AD AE BC BD BE CD CE DE 3.162 7.071 6.708 4.000 8.944 7.810 7.071 2.236 5.099 6.083 Same cluster: Shortest distance between two respondents Euclidean Distance AB AC AD AE BC BD BE CD CE DE 3.162 7.071 6.708 4.000 8.944 7.810 7.071 2.236 5.099 6.083 Same cluster: Shortest distance between two respondents Ch 1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 A B C D E Low High Low High Marketing (X1) A c c o u n t i n g ( X 2 ) Cluster 1 Cluster 2 Ch 1 A B C D E Low High Low High Marketing (X1) A c c o u n t i n g ( X 2 ) Cluster 1 Cluster 2 4.000 5.099 Single linkage: Distance between E and the closest members in Clusters1 and 2 Ch 1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 A B C D E Low High Low High Marketing (X1) A c c o u n t i n g ( X 2 ) Cluster 1 Cluster 2 4.000 5.099 Single linkage: Distance between E and the closest members in Clusters1 and 2 Ch 1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 A B C D E Low High Low High Marketing (X1) A c c o u n t i n g ( X 2 ) Cluster 1 Cluster 2 7.071 6.083 Complete linkage: Distance between E and the furthest members in Clusters1 and 2 Ch 1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 A B C D E Low High Low High Marketing (X1)...
View Full Document

This note was uploaded on 06/18/2011 for the course MGT 600+ taught by Professor Shen during the Spring '11 term at Saint Joseph's University.

Page1 / 86

08_Chapter 09(1) - Click to edit Master subtitle style Ch 1...

This preview shows document pages 1 - 21. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online