Intro, reasons behind compilation

Data

Information was compiled based on a variety of variables and placed into a tabulated spreadsheet. The amount of accumulated variables differed only slightly for each of the three years, as it was dependent on the availability of the data for each team.

For 2008, there were 33 primary variables originally created which included the following:

Area (where the team registered under), university/team name, medal/prize/final6, university citation score, university rank, projected budget, budget at the time of registration, university endowment, if school was public/private (USA only), academic sponsors total, biotech sponsors total, other sponsors total, number of biobricks submitted, if a team withdrew, total students, students with no data, biology students, chemistry students, engineering students, mathematics/ computer scientist students, physics students, medical students, art students, social scientist students, total advisors, engineering advisors, biology advisors, medical advisors, physics advisors, chemistry advisors, mathematics/computer scientist advisors, art advisors.

2009 incorporated one extra variable, which looked at the team’s predicted award versus the award received by the team itself. This information wasn’t accessible to process for 2008, as at this point judging forms weren’t employed online for the competition in 2008. Finally, university research score was included in the 2010 selection.

The next step in the data analysis was to create an ordinal measurement of the medal criteria and the predicted versus awarded medals, in addition to creating a student to advisor ratio. An ordinal scale is where a particular ranking order is given to the data. The scaling for the medal criteria, so that we incorporated teams that withdrew into our samples, is as follows:

0 – Team Withdrew 1 – No medal awarded 2 – Bronze 3 – Silver 4 – Gold 5 – Finalist 6 – Grand Prize Winner

This scale now allows us to analyse the relative success of each team.

Also the monetary variables were all altered by changing the currency base into US dollars and historical exchange rates were used to keep these values comparable, at a specific time of each respective year. (http://www.xe.com/ict/?basecur=USD&historical=true&month=3&day=25&year=2010&sort_by=name&image.x=32&image.y=14&image=Submithttp://www.xe.com/ict/? basecur=USD&historical=true&month=3&day=25&year=2010&sort_by=name&image.x=32&image.y =14&image=Submit)

In total, 303 iGEM teams worth of information was collected over the past three years.

What data was compiled AND how data we chose to work with, programs used, acknowledgments

Analysis

describing stats, etc.

What does this mean for iGEM?

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