This goal discusses how to Analyze data quantitatively and draw appropriate conclusions. The first thing that comes to mind when looking at this topic is BIOL 251 which is an introduction to ecology and evolution, because of the high number of datapoints that we had. The experiment that was done in BIOL 251 was seeing the difference in biodiversity between forests and grassland. 25 pitfall traps were step in both forest and grasslands. The group would go to buffalo creek and check how much biodiversity was in each cup and record the cloud coverage, precipitation, and humidity of that day. This went on for around three weeks until we got all our specimens. We had all our data on our notebooks then transferred them to excel. The graphs were all done using the graphical analysis that excel has. Using excel was not bad and after taking MATH 171 I would consider myself an excel data analysis master but I always wanted to learn R. This changed once I took BIOL 341. This class discussed a more advance ecology than 251. In this class we talked about fragmentation which really interested me. This excitement for fragmentation made me want to do a lab project looking at the differences in distance in man-made fragmentation which was the bike trail. Five pitfall traps were location between the man-made fragmentation and one more the same distance of the man-made fragmentation away from the other pitfall trap. This sparked my interest because fragmentations on a larger scale like deforestation cause lower biodiversity, so I wanted to test this on a smaller scale. The same thing was done as the first experiment, the cups were checked every other day for three weeks until enough data was collected. After three weeks and all data was collected it was time to do te data analysis. The really cool thing about doing data analysis now is getting to use R studio to make my graphs and find my p-values. I took this course along with MATH 301 and I really enjoyed using R studio at the time. I believe that I learned more about statistical values and doing statistical graphs from R than I ever did using excel. I am very proud of having to learn both excel statistical analysis and R studio because those are two skills and techniques I can use in graduate school. These are also two skills I can use on my resume and are highly used in laboratory. If I could do anything different in my data quantitative skills, it would be to take MATH 171 along side or before I take my 200 level BIOL classes because I did not learn anything when I used excel in BIOL 251. Now that I have acquired these two skills to interpret and draw conclusions. I can now accurately either survey people a large amount of people and be able to run statistical analysis on R and excel to draw conclusions from. 

https://docs.google.com/presentation/d/1KtdVsT8VJYbYf8gDKrpwT-DtG2ErxkIrz77oHj2NFnU/edit#slide=id.p1

https://docs.google.com/presentation/d/1FBCTjajxrhmLQShyikjcIU6n6vqJNJtx/edit#slide=id.p1