Question
A consultant has been asked for advice about remediating the sites of20 chemical factories abandoned during a war in a developing country. No records are
A consultant has been asked for advice about remediating the sites of20 chemical factories abandoned during a war in a developing country. No records are available about what was manufactured at the different sites. He decides to start by carrying out chemical analyses on soil samples from each of the sites and measuring the concentration of 11 different substances (Substl to Substll) in each:
Substl to Subst3 are common inorganics
Subst4 to Subst7 are common organics
Subst8 to SubstlO are associated with the textile industry
Substl1 is associated with the manufacture of explosives
At this stage he does not know how many different types of chemical factory there are, or which factories produced what.
Data
Factory | Subst1 | Subst2 | Subst3 | Subst4 | Subst5 | Subst6 | Subst7 | Subst8 | Subst9 | Subst10 | Subst11 |
1 | 3.3 | 1.95 | 84 | 0.0388 | 8.9 | 3.5 | 625 | 0.7 | 112 | 3.6 | 1.0 |
2 | 5.2 | 3.00 | 159 | 0.0325 | 8.1 | 2.6 | 427 | 2.4 | 86 | 2.8 | 2.0 |
3 | 3.8 | 1.60 | 90 | 0.0400 | 9.5 | 3.4 | 741 | 3.4 | 152 | 5.0 | 51.5 |
4 | 5.6 | 2.85 | 156 | 0.0288 | 7.8 | 2.6 | 485 | 9.2 | 244 | 8.2 | 1.7 |
5 | 5.3 | 2.60 | 180 | 0.0313 | 8.4 | 2.4 | 472 | 11.0 | 224 | 7.3 | 51.6 |
6 | 5.5 | 2.65 | 171 | 0.0325 | 8.9 | 2.7 | 565 | 2.3 | 136 | 4.4 | 50.0 |
7 | 4.0 | 1.65 | 81 | 0.0288 | 8.6 | 3.7 | 677 | 0.7 | 65 | 2.4 | 2.2 |
8 | 3.5 | 1.60 | 99 | 0.0375 | 8.6 | 3.1 | 645 | 6.8 | 230 | 7.8 | 50.8 |
9 | 5.6 | 2.90 | 153 | 0.0325 | 7.9 | 2.2 | 510 | 2.4 | 116 | 3.6 | 52.4 |
10 | 3.0 | 1.55 | 114 | 0.0400 | 9.4 | 2.6 | 633 | 6.2 | 203 | 6.3 | 1.2 |
11 | 5.2 | 2.80 | 171 | 0.0300 | 8.2 | 2.8 | 550 | 2.6 | 133 | 4.3 | 51.0 |
12 | 3.5 | 1.95 | 75 | 0.0325 | 8.7 | 3.3 | 563 | 6.0 | 194 | 6.1 | 2.0 |
13 | 3.5 | 1.85 | 84 | 0.0363 | 9.2 | 3.2 | 599 | 9.6 | 274 | 8.2 | 3.9 |
14 | 5.6 | 2.85 | 156 | 0.0338 | 8.1 | 2.6 | 429 | 10.0 | 250 | 8.2 | 2.7 |
15 | 3.1 | 1.65 | 108 | 0.0388 | 8.5 | 3.1 | 672 | 8.8 | 217 | 7.4 | 51.0 |
16 | 4.0 | 1.55 | 87 | 0.0313 | 9.2 | 3.2 | 664 | 4.4 | 115 | 4.2 | 3.2 |
17 | 5.4 | 2.70 | 171 | 0.0263 | 8.8 | 1.8 | 502 | 0.9 | 43 | 1.9 | 2.5 |
18 | 5.5 | 2.60 | 174 | 0.0238 | 8.2 | 1.8 | 486 | 10.5 | 278 | 8.4 | 1.0 |
19 | 5.5 | 2.60 | 174 | 0.0350 | 8.1 | 2.8 | 607 | 1.1 | 60 | 2.6 | 1.4 |
20 | 3.5 | 1.50 | 105 | 0.0400 | 9.6 | 3.1 | 793 | 13.8 | 300 | 9.2 | 1.6 |
1. Run the Principal Component Analysis in MINITAB or SPSS
2. Screen capture of the process.
3. Interpret the results using the Score Plot.
4. State the appropriate conclusion.
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