To increase the validity of his data, Mario could:
1. Add a 0 hours control: Implementing a control group that does not receive any light would be very beneficial. This would provide a baseline to compare how much oxygen is produced when there is no light at all. With this baseline, Mario could better determine the effect that the light has on oxygen production.
Let’s go over why the other options might not be as effective:
- Reduce the number of plants: Reducing the number of plants would likely decrease the reliability of the data, as a larger sample size generally leads to more accurate and generalizable results.
- Remove the 1 hour group: Removing any data point, including the 1 hour group, would reduce the range of data Mario collected, making it more difficult to analyze the relationship between light exposure and oxygen production.
- Measure the oxygen in liters: Changing the unit of measurement does not influence the validity or reliability of an experiment. Whether the oxygen is measured in milliliters or liters, the relationship between light exposure and oxygen production remains the same.
Therefore, adding a control group with 0 hours of light would most effectively increase the validity of Mario’s experiment.
