A data analysis is where you discuss and interpret the data collected from your project and explain whether or not it supports your hypothesis. The analysis may discuss mistakes made while conducting the experiment or ways in which the project could be improved in the future.
An analysis should begin be explaining what happened in the experiment. Outline the process you used and the data that you collected. After you have described what happened in each experiment, you can begin discussing what can be learned from the data. Look at the experimental evidence collected and talk about why you think you got these results. Be certain to ask how the data relates to your hypothesis. It is helpful to look for patterns in the data that either support or negate your original hypothesis. Discuss whether you were right or wrong. Ask yourself if the results make sense, and if they do not, explain why you disagree with the results. Discuss whether the tools used, the way the data was collected, or other factors that you believe may have caused incorrect results. The analysis is the place to state disagreements with the data, but sufficient evidence must be present. Do not change your hypothesis as you write your analysis even if it does not match the evidence collected. Instead discuss whether you accept or reject your hypothesis, and what that means.