The data that was recorded supports the hypothesis by showing that as the aquatic plant moved closer to the heat lamp, the rate of bubbles per minute …show more content…
would raise.
To further explain, while the plant was placed 100 centimeters away from the light source while the lamp was turned off it was recorded that no bubbles were produced. This acted as the control, in order to provide a standard comparison for the trails to come. The plant was then moved 25 centimeters closer to the lamp (Distance 2: 75cm), and roughly 1.6 bubbles appeared each minute. This means that there was an average of 5 bubbles overall after the three trials. While comparing the data from these two distances one can clearly see that as the light shining on the plant became more intense, more oxygen was produced by the plant. The rate of bubbles per minute jumps from 1.6 to 15.86 when the plant was placed 50 centimeters away from the heat lamp. The highest amount of bubbles produced with this distance was 55, and the overall average for the three trials was 47.6. These numbers show that the average number of bubbles increased by about 42 bubbles. For the final leg of the experiment the elodea plant was placed 25 centimeters away from the light source, and after all three trials the rate of bubbles per minute came out to be 24.86. This was the
distance with the most intense amount of life, which makes sense as the average amount of bubbles was 74.6. One can conclude from this data and evidence that light intensity is a limiting factor of photosynthesis. This is because depending on the intensity of the light, there will be either a large or small amount of oxygen produced in the process. Another conclusion that can be made is that the hypothesis was indeed accepted due to the fact that as the light became closer to the plant and got more intense, the production rate of the products of photosynthesis increased greatly. One can support these conclusions by referring to the data listed.
During this experiment one factor that could have impacted the data and results includes the amount of trials taken. This is because a higher number of tests would make the averages of bubbles more accurate, as with only three trials it is likely that there was an outlier in at least one trial that threw off the rate as well as the average. Additionally, due to a misunderstanding, the bubble observer switched to a different person in the middle of a trial. There is a high chance that by changing the bubble observer to a different person an error in the data was made present. To further explain, between trial two and three of the third distance listed on the data table, there was a jump of 29 bubbles. This number raised the average as well as the rate. To fix the first error listed, the experiment should be altered so that more trials will be required for each distance, allowing more accurate results, and a larger amount of evidence. Secondly, when errors such as a switch in the observer occur, it would be better to redo the trial to get correct data, and ideal to avoid such a mishap in the first place.