From the data obtained in Tables 1-3, we were able to plot multiple graphs using excel. These graphs give a better representation of the data as seen in Figures 1-9. It can be seen that each figure shows a slight increase in CO2 production, which signifies a possible change in metabolic rate. Figures 4 and 7 show a relatively large change between the control and fox urine. The changes in slope between theses two are 0.0267 for Figure 4’s slopes and 0.0192 for Figure 7’s slopes. Figures 1-3, 5-6, and 8-9 all showed a change, but not as large as their counterparts. This was due to the fact that the mice were usually cleaning themselves at in this group during the control. Figure 8 shows the smallest change between the two groups with a value of 0.0002. This figure represents a Cage A Yellow Mouse, which also had one of the lower body weights. The statistics from Tables 1-3 we were able to find the amount of CO2 produced in mL for each mouse as seen in Table 4. These statistics …show more content…
Using an online program from Vassar Stats we were able to calculate the statistics necessary for our experiment. The Two Sample t-test program was initiated on the website, and using the data from Table 5 the program was ran with the Correlated Samples option selected. This was selected due to the fact that the mice from our control group were also used in the experimental group. All of the information provided by this tool can be in Figures 10-12. The major value from all of this is from Figure 11 and it was our two-tailed P-value. This value was 0.019589 and with this statistic we were able to look at our hypothesis again. We could successfully conclude that our null hypothesis of the urine having no effect on the mice was wrong. This is because of P-value is <0.05 and represents that are data was statistically