# BME100 f2015:Group2 1030amL2

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# OUR TEAM

 Name: Cynthia Crockett Name: Amar Joshi Name: Gage Schrantz Name: Xiaoyu Chen Name: Colleen Rice Name: Anton Voronov

# LAB 2 WRITE-UP

## Descriptive Statistics

Human Study

 0 mg 5 mg 10 mg 15 mg Average (mg) 3.834 8.932 61.622 657.941 Standard Deviation (mg) 1.523 1.594 30.111 212.943 Standard Error (mg) .482 .504 9.522 67.338

Rat Study

 0 mg 10 mg Average 10.814 11.112 Standard Deviation 2.226 7.403 Standard Error .9953 3.311

Human Experiment

Rat Experiment

## Analysis

Human Experiment

• Using the ANOVA Test we determined the results were significant

• Using the post-hoc test we determined that there was a significance between each of the groups, as they relate to each other

Rat Experiment
• Used the T-test instead of the ANOVA, as we only had two variables to compare.

• Since the significant value we got from the T-test was greater than 0.05, it was not significant.

• The P-test was relatively close to -1, of which indicated that there was a negative correlation with the data.

## Summary/Discussion

As the dosage increased by 5mg the inflammation protein levels also increased exponentially in humans. We decided to choose the ANOVA test for this this experiment because we had more than two variables. When we did the post-hoc to see if the results were significant, we found out that they were significant between the groups with greater than 95% confidence. The medicine does significantly increases inflammation protein levels in humans. In contrast, in the lab rat experiment, we used the T-test as there were only two variables. We then calculated that the results were not significant as it had less than 95% confidence. Additionally, the P-Value indicated that there was a general negative correlation between the two variables. In other words, the medicine does not significantly increase the inflammation protein levels in rats.