We have analyzed 12 different data sets, including intraspecific and interspecific, to compare the fitness of models that can be applied to variance or occupancy prediction. We used 2 methods at two numerical scales to study these six phenomenological models, three for variance prediction and three for the occupancy. Regardless of the significance of the differences, we noticed that various results came out when we applied different methods or scales.
During the research, we tried different approaches and to test the data and we tried different statistics as measurement. Deciding the research approach and statistics was the struggle. So we analyzed the data using every possible approach and then refined the approach again and again.
I have learned a lot from this project, not only the knowledge about both statistics and ecology, but also my software R, skills since R is the software we used to process the research. Moreover, the research teaches me that the more you think and the more you practice, the closer you will get to the truth beneath those data, which means attitude can lead us to the result. I think attitude is as important as the scientific knowledge and technical skills.
This research definitely has a great impact on my future plan. It let me know what I really love, data analysis. I am looking forward future researches that building different models to test the data and find out what the data really tell us.