A CIESE Collaborative Project

# Analyze the Data

## Step 1: Plot the Data

Make 3 graphs and 1 chart using the results from all schools to see which variable in the experiment has the strongest correlation to boiling point. The variable that has the strongest correlation to boiling point is the factor which is most responsible for making water boil.

It is recommended that you use the ''checked" data for your analysis. This data has been checked and verified by the project leader. Using this data will ensure that when students analyze the data they will not be mislead by any unreasonable, unverified, or incorrect data. However, comparing the "unchecked" database to the "checked" database might be a good exercise for advanced students. They could determine if all the "unchecked" data makes sense. Scientists NEVER throw out data without looking into why there might be strange results and this might be a good lesson for your students. Students are welcome to use the project Discussion Area to question other students about their results and to provide recommendations to the project leader about what to do with "questionable" data.

The graphs and chart that students should make are:

1. Graph boiling point (y-axis) vs. volume of water (x-axis)
2. Graph boiling point (y-axis) vs. elevation (x-axis)
3. Graph boiling point (y-axis) vs. room temperature (x-axis)
4. Make a chart that shows the types of heating devices used and the boiling points reached using each kind of device

Need Help? Take a look at this Graph Example and Chart Example.

## Step 2: Analyze the Data

Draw a "line of best fit" or "trend line" through the data in each of the 3 graphs. In some spreadsheet programs, this can be done automatically. But sometimes it needs to be done by hand. Students should not "connect the dots" but, rather, draw a straight line which represents the trend in the data. Roughly half of the data points should be above the line and half below it.

If many of the data points lie on or close to the line of best fit, you can rest assured that there's a good strong relationship between the two variables. In other words, if the line of best fit accurately represents the trend in data, then there is probably a strong correlation between the two variables. If the data is scattered and it is difficult to draw a line of best fit or the data doesn't appear to lie on or near the line of best fit, then there probably is no correlation between the two variables you have graphed.

Optional - Determine the correlation coefficient to help determine the strength of the relationship.

Optional - Once you have the line of best fit, you can figure out the equation of the line. Knowing the equation of the line will help you predict what the boiling point will be at other points. You could even predict what the boiling point might be for a school in a different location. Find a school at that location to do the experiment and confirm your theory.

Looking at the chart that you constructed, if you see that each type of device always has a boiling point close to the same number, then there probably is a good correlation between boiling point and heating device. If the boiling point varies from device to device, there probably isn't any strong relationship between the two.

## Step 3: Draw Conclusions

Based on your graphs and chart, figure out which factor in the experiment (volume of water, elevation, room temperature, or heating device) has the strongest correlation to boiling point. Do the experimental results support your hypothesis? Why or why not? Share your class results by writing a short Final Report and posting it in the Discussion Area.