To increase the validity of Mario's data in his photosynthesis experiment, it is crucial to have a baseline to compare the results effectively. Let's consider the options provided:
1. Reduce the number of plants:
- Reducing the number of plants would not increase the validity of the data. It would actually reduce the reliability and the statistical significance of the results since fewer samples would not represent the population as well.
2. Remove the 1 hour group:
- Removing the 1 hour group would eliminate valuable data on how the amount of light affects photosynthesis at lower light levels. This would not help in increasing the validity but rather decrease the comprehensiveness of the study.
3. Add a 0 hours control:
- Adding a control group that receives 0 hours of light is an essential step in scientific experiments to establish a baseline measurement. The control group helps in comparing the results to a standard where no treatment (in this case, no light) is applied. This allows you to see the effect of light exposure on photosynthesis more clearly by comparing it to a condition where no photosynthesis due to light exposure should occur. Therefore, this would significantly increase the validity of Mario’s data.
4. Measure the oxygen in liters:
- Measuring the oxygen produced in liters instead of milliliters would not inherently increase the validity of the data. It is just a different unit of measurement, and since the volumes measured are small, milliliters is an appropriate and precise unit.
Given these considerations, the best way for Mario to increase the validity of his data is to add a 0 hours control group. This allows for a clear baseline comparison and aids in precisely understanding the impact of different light exposures on photosynthesis.
Thus, the most suitable action for enhancing the validity of the experiment is:
- Add a 0 hours control.
