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View recorded webinars:
http://bit.ly/particlewebinars
Arundas is a mechanical engineer with over 8 years of experience in MEP project coordination, engineering, and management in GCC and India. He has expertise in HVAC, plumbing, electrical, and low current systems, as well as commissioning, quality control, and project management. Arundas is proficient in AutoCAD, MS Office, Project, and various industry standards and codes. He is seeking a position utilizing his skills in the construction industry.
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The ViewSizer® 3000 offers the ability to visualize nanoparticle colloids without requiring calibration standards or knowledge of any particle material properties, such as refractive index. It was developed by MANTA – the Most Advanced Nanoparticle Tracking Analysis – and offers the user an unprecedented ability to count and size highly polydispersed samples, such as milk, sea water, or blood plasma.
View recorded webinars:
http://bit.ly/particlewebinars
Arundas is a mechanical engineer with over 8 years of experience in MEP project coordination, engineering, and management in GCC and India. He has expertise in HVAC, plumbing, electrical, and low current systems, as well as commissioning, quality control, and project management. Arundas is proficient in AutoCAD, MS Office, Project, and various industry standards and codes. He is seeking a position utilizing his skills in the construction industry.
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This document summarizes Makana Tavares' background and goals. It discusses their upbringing in Hawaii and values of community well-being. Their goals include seeing Hawaii become more self-sufficient in food and energy and embracing its multicultural identity. They are now a rising junior at Brown University studying anthropology and volunteering in their community. Their experiences have shaped their desire to work in non-profits and grassroots organizations to better meet social needs.
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1. Quick Cluster
Notes
Output Created 29-JAN-2013 01:47:30
Comments
Active Dataset DataSet1
Filter <none>
Weight <none>
Input
Split File <none>
N of Rows in Working 61
Data File
User-defined missing values are
Definition of Missing
treated as missing.
Missing Value Handling Statistics are based on cases with no
Cases Used missing values for any clustering
variable used.
QUICK CLUSTER @40Dollars
@20Dollars @10Dollars Bookbag
Fannypack Pocket @5Min @2Min
@0.5Min Difficult Medium Easy
/MISSING=LISTWISE
Syntax
/CRITERIA=CLUSTER(2)
MXITER(10) CONVERGE(0)
/METHOD=KMEANS(NOUPDATE)
/SAVE CLUSTER
/PRINT ID(SerialNo) ANOVA.
Processor Time 00:00:00.13
Resources Elapsed Time 00:00:00.14
Workspace Required 2064 bytes
Variables Created or Cluster Number of Case
QCL_2
Modified
[DataSet1]
Iteration Historya
Iteratio Change in Cluster Centers
n 1 2
2. 1 41.032 49.595
2 5.321 4.166
3 3.517 2.128
4 3.092 1.593
5 2.988 1.472
6 1.267 .546
7 1.487 .628
8 1.679 .634
9 .000 .000
a. Convergence achieved due to no or
small change in cluster centers. The
maximum absolute coordinate change
for any center is .000. The current
iteration is 9. The minimum distance
between initial centers is 91.740.
Final Cluster Centers
Cluster
1 2
@40Dollars -6.50 -14.97
@20Dollars 1.47 -.06
@10Dollars 5.03 15.03
Bookbag -30.56 -5.99
Fannypack 4.00 1.06
Pocket 26.57 4.93
@5Min -8.53 -14.90
@2Min 1.76 -1.53
@0.5Min 6.77 16.43
Difficult -7.94 -9.64
Medium 1.74 3.68
Easy 6.20 5.96
ANOVA
Cluster Error F Sig.
Mean df Mean df
Square Square
@40Dollars 874.478 1 80.080 58 10.920 .002
@20Dollars 28.528 1 14.532 58 1.963 .167
3. @10Dollars 1219.354 1 74.877 58 16.285 .000
Bookbag 7359.932 1 39.751 58 185.150 .000
Fannypack 105.531 1 30.121 58 3.504 .066
Pocket 5702.912 1 42.451 58 134.341 .000
@5Min 494.528 1 81.667 58 6.055 .017
@2Min 132.427 1 49.250 58 2.689 .106
@0.5Min 1138.354 1 113.215 58 10.055 .002
Difficult 35.205 1 89.322 58 .394 .533
Medium 45.987 1 27.888 58 1.649 .204
Easy .726 1 76.817 58 .009 .923
The F tests should be used only for descriptive purposes because the clusters have been chosen
to maximize the differences among cases in different clusters. The observed significance levels
are not corrected for this and thus cannot be interpreted as tests of the hypothesis that the cluster
means are equal.
Number of Cases in each
Cluster
1 17.000
Cluster
2 43.000
Valid 60.000
Missing 1.000