Submit Your Results
Click on the Project Data link on the left menu bar to submit your results. Below is the information that you will be asked to provide. Some of the information is optional.

• School Name (required)
• School District (optional)
• City (required)
• State or Province (required)
• Country (required)
• Continent (required)
• Latitude and Longitude  (optional - see the Reference Material section for help)
• Teacher Name (optional)
• Teacher Email Address (optional)
• Subject or grade level (optional)
• Number of students using project (optional)
• Class Average Daily Water Use (required - see note below)
• Water Flow Direction (optional - see Mind Boggler activity)

Note: Since different countries use different units to measure water use, we would like to display the water use data in both gallons per person per day and liters per person per day. On the data submittal form you will be prompted to enter your water use in EITHER gallons per person per day OR liters per person per day. When you submit your data, the other value will be automatically calculated.

Look at Other Class Results
Click on the Project Data link on the left menu bar to view the results submitted by other classes. You can search the database or download it to your computer. You may also want to look at archived data submitted in previous years which can be found on the same web page.The more data the better!

Analyze the Results
Look closely at all the data. You may need to print out the database but it might be rather long! Depending on what your prediction was, you may need to look at data from specific locations or you may need to do a bit more averaging of some of the data. Try to use tables or charts to help organize your data and to display your results.  Look closely at the data other schools submitted. Are there any schools that seem to have unreasonable results? Why might that be? After analyzing the data, determine if your hypothesis was correct or needs to be changed a bit. If so, develop a new hypothesis (and  new prediction) and look at the data again.