BME100 s2015:Group2 12pmL2
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OUR TEAM
LAB 2 WRITE-UPDescriptive Statistics
Results
AnalysisFor the study with Humans, the ANOVA test was used because there were more than 2 data sets to be compared. Then, the Bonferoni Correction test was used by implementing the t-test to find the corrective p-value for each of the comparisons (example: 0mg vs. 5mg and 0mg vs. 10mg). There were six comparisons total which were based off of the four different groups. These values were used to determine the significance between the the p-value of 0.0083 (0.05 divided by 6) with the t-test value for each of the 6 comparisons. The values were deemed significant because of the great differences between the T-Test Value and the corrected P-Value.
During the rat study, the dosage amount of 0mg changed the amounts of inflammotin within the rats was equal to the amount of inflammoton with the 10mg dosage, both averaging out to 10.516 for 0mg and 11.112 for 10mg which shows the deviation to be insignificant and making it statistically insignificant. Result from the standard deviation shows that the level of inflammotin within the test subjects with 0mg and 10mg dosage varied.
Summary/DiscussionFor the Rat test the T-Test was used to analyse the data, the T-test was chosen because the rats experiment only included two data sets-so ANOVA was not necessary. In the Rat test, there was no significant statistical difference, and so there was no importance in the difference between 0mg and 10mg in rats. However, in the human study where 0, 5, 10, 15 mg were used there was a significant difference between each of the 4 doses. In the human inflammotin test, there were six comparisons used to test for variance. The human inflammotin test needed to use the ANOVA because there were 3 data sets that were tested. |