Analyzing Primary Production Data: Key Findings from Experiment

1. Data set Year 0 plot 2. Data set year 3 plot P Value 0.5673 which is more than 0.05 P value 0.0032 which is less than 0.05 Meaning there is no significance difference This means that there is a significant between the control and experimental plots difference between the control and That were tested on experimental plots that were tested 1. How did you rank the four graphs about Compound X in the lab manual under the “Sample Distributions” header? What was your reasoning for how you decided to rank them? Your ranking: B-1 D-2 A-3 C-4 Your reasoning: B is the most confident because the means are not close together and they are far apart compared to C where they have almost the same mean and the graphs are overlapping each other as for the other graphs such as D and A their means are also significantly different but D seems to be a little more farther apart then A is so I put the D graph right before A but I am pretty confident they are different environments 2. From the “What is a t-statistic” section of the lab manual, describe what each boxed quantity in the t-statistic equation represents (A-D). Part A. This part of the equation is representing the mean of the experimental Part B. This part of the equation is representing the mean of the control Part C. This part of the equation is representing the standard deviation of the experimental

Part D. This part of the equation is representing the standard deviation of the control 3. From the “What is a t-statistic” section of the lab manual, what were your answers to the questions below the graph showing bacterial cells/ml? Include an explanation of your reasoning. The t-statistic will be Large , because there is a pretty good difference in the lines of the graph The p-value will be small , because in stats if there is a higher t value there is going to be a smaller p value The statistical conclusion will be Significant , because In stats when there is a small enough p value this would mean that there is a difference in the set of data 4. Insert a photograph of the graph you drew on the large paper during lab during the “Graphical Representations of Data” discussion (instructions are under that header in the lab manual). Why did you choose this type of graph? After the class discussion, which type of graph do you think would be the best to use with these data? Explain your reasoning. My group chose to create the type of graph because in our opinion we have always been used to more bar graphs and felt more comfortable creating a bar graph then any of the other ones. The different colors help us distinguish which data was the control and which ones was experimental After our discussion in class the best type of graph to use was probably a line graph because the other groups were able to get their data onto the paper more

efficiently and it was more clear and precise. Two line graphs one for the control and one for the experimental looked the most neat and organized 5. What features should be on a graph to clearly communicate results (based on the in-class discussion)? The features that should be clear on the graph to communicate results are that the x and y axis should be labeled along with the title and any labels needed to clear up research information. You should always have units and make sure to color code your graph with the corresponding color code key to let the audience know what color is for what meaning. If you have any variables be sure to include a key for that also and a summary statistics such as the average and measure of data spread. 6. From the "Primary Production Across Time" part of the lab document, describe the pattern you observed when you graphed primary production across time for the Cedar Creek NutNet plots. Were the fertilized (NPK) plots different from the control plots? Explain your answer, including what you learned from the p values and information about the slopes of the best fit lines. For the Cedar Creek NutNet plots looking at the p values you are able to tell that the fertilized plots formed a pattern. The fertilized plots produced more live biomass than the other plots on the graph which is the control 7. From the "Primary Production Across Space" part of the lab document, how did the fertilization effect vary by latitude? What conclusions did you draw, based on your graph? The conclusions I can draw based on the graph is that the higher the latitude the more fertilizer had an effect on the plots land they were used on. 8. In the "Comparing the Impact of Different Fertilizers" section, what were your conclusions about the effect of the different fertilizer treatments (N, P, and K) on biomass production at each of the 4 sites? After comparing the fertilizer treatments of N,P and K I found that the only treatment that seemed to have helped the land was Nitrogen. While Nitrogen seemed to be helping it also seemed that Phosphorus was the nutrient that was limiting the effects on the other nutrients. And the other didn't seem to stray too much from each other in any department 9. Paste in your data table from the "Comparing the Impact of Different Fertilizers" section (or upload it as a separate file if necessary).

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Site Name Treatment Type (control, N, P, or K) Slope Estimate Bunchgrass Control 5.4343939 Cedar Creek Control 8.3154727 Sedgwick reserve Control 27.212773 Spindletop Control 7.9987879 Bunchgrass K -0.704697 Cedar Creek K 14.899091 Sedgwick reserve K 26.425242 Spindletop K 41.775152 Bunchgrass N -24.67785 Cedar creek N 15.650855 Sedgwick reserve N 57.996424 Spindletop N 5.1724242 Bunchgrass P 10.055303 Cedar Creek P 17.160455 Sedgwick reserve P 29.964939 Spindletop P 20.103636 10.Data analysis is an important part of doing science, and as scientists we often have to choose the correct tools for performing our data analysis. In this lab, you used JMP software to do your data analysis. What benefits did JMP have compared to other software you have used (Excel, R)? What drawbacks were there? I believe that JMP was easier to navigate and learn its tools. I learned and got through the material faster and with ease. It is more user friendly than other software such as R or excel but I do think that R does a better job with the amount of variety and options they have with graphs and data tables as they create clearer graphs and give you more to work with.

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primary production post lab

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