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Sample Results

To start an experiment the first step is to ask a question, create a hypothesis, design an experiment that tests your question, collect your data and finally analyze it and come up with a conclusion. To collect data from an experiment similar to ours, plot a site where you will take soil samples and record these locations, we took 10 samples per day. Then collect these soil samples and label them with their location. Using these samples test for Ferric iron, mold and bacteria levels and make a data chart.

Here is a sample data chart with two days' worth of results:

	Iron (ppm)	Mold (#/cc)	Bacteria (#/cc)
1	7.5	300	840000
2	7.5	1000	150000
3	7.5	10000	320000
4	2.5	500	78000000
5	16.25	3000	7000000
6	16.25	1000	36000000
7	7.5	10000	32000000
8	7.5	1000	43000000
9	16.25	40000	20000000
10	7.5	40000	500000
11	2.5	6000	700000
12	62.5	2000	1040000
13	2.5	100	120000
14	7.5	100	600000
15	2.5	2300	380000
16	7.5	500	740000
17	2.5	300	600000
18	16.25	300	5000000
19	2.5	0	1700000
20	7.5	20000	730000

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After collecting your data you should organize and analyze your results. To analyze our data we calculated the averages of the bacteria, mold and iron levels from both quadrants each day. Averages are important because they provide a simplified list of the data for easy analysis.

Here is an example of an averages chart:
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We also ran t-tests on each data list to calculate their statistical significance. (For further explanation of a t-test click here) T-tests are important because they help evaluate the statistical significance of the data.

Here is an example of a t-test results chart:

	Quad 2			Quad 4
	Day 1-Day 2	Day 1- Day 3	Day 2- Day 3	Day 1- Day 2	Day 1- Day 3	Day 2- Day 3
iron	0.576	1	0.576	0.2898	0.946	0.565
mold	0.698	0.8155	0.9237	0.203	0.192	0.995
bacteria	0.3346	0.3932	0.4373	0.0296	0.029	0.821

Another thing you can do to statistically analyze your data is to make a scatter plot, run a line-of-best-fit and calculate the r² value. This will tell you the strength of the correlation of the two variables you are comparing. This test can be done on a TI-84 Plus calculator (for further instructions click here)

Here are a few examples of scatter plots:
The effect of the amount of Ferric Iron on the levels of Mold
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                                                                                  The effect of the levels of Bacteria on the amount of Ferric Iron
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To keep your data and stats organized is to create a data table and graphs. Graphs and charts give you a visual representation of your data and can help make it easier to analyze. Here are examples of our data tables, graph and charts.

(P.S. Here is a helpful hint when making graphs: use the averages of the data for a simpler graph.)

Here are a few of our graphs: