BME100 s2015:Group18 12pmL2

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Contents

OUR TEAM

Name: Walter C. Bregon
Name: Walter C. Bregon
Name: Jenna M. Taras
Name: Jenna M. Taras
Name: Nathan K. LeFort
Name: Nathan K. LeFort
Name: Abdurrahman Darwish
Name: Abdurrahman Darwish
Name: Hau Nguyen
Name: Hau Nguyen
Name: Eyerusalem
Name: Eyerusalem

LAB 2 WRITE-UP

Descriptive Statistics

Experiment 1

Human Study

Image:Bme100_lab2_stats1_2.png


Image:Bme100_lab2_stats2_2.png


Rat Study

Image:Bme100_lab2_stats3_2.png

Experiment 2




Results (Graphing)

Experiment 1

Image:Bme100_lab2_humangraph2.png‎

Experiment 2

Image:Bme100_lab2_ratgraph2.png




Analysis (Inferential Statistics)

Our group chose to use ANOVA to analyze and investigate the differences between the four groups in our human data, because we were comparing more than two groups. The t-test analyzes and investigates the differences (in means and variations) of only two groups and the ANOVA does the same but for more than two groups. We chose the t-test for the rat data because there are only two groups to compare; the rats getting the 0 mg dose of LPS and the rats getting the 10 mg dose of LPS. There were four groups in the human study getting 0 mg, 5 mg, 10 mg, and 15 mg of LPS, respectively.

After doing the ANOVA test for our human study data, the result showed our p-value was less than 0.05 which means there is a statistical difference between our group data. We were now required to use the t-test to compare our human data in more depth (with in each of the four groups). We did a total of 6 post-hoc t-tests (0 mg vs 5 mg, 0 mg vs 10 mg, 0 mg vs 15 mg, 5 mg vs 10 mg, 5 mg vs 15 mg, and 10 mg vs 15 mg groups)that will then tell us if there is a statistical difference between each of these 6 groups. After calculating the Bonferroni Correction (0.00833333), we used this corrected p-value to determine if each of the 6 t-tests was significant or not. All six of the p-values was less than our Bonferroni Correction which told us that there is significant statistical difference within the four human groups.

The t-test we ran on excel for the rat study gave us a p-value that was greater than 0.05 which told us that the two rat groups that we tested had no statistical difference in their results.


Experiment 1

Human Anova Test

Image:Bme100_lab2_anova.png

Human Post-Hoc Tests (T-Tests)

Image:Bme100_lab2_humanttest.png


Experiment 2

Rat T-Test

Image:Bme100_lab2_ratttest.png



Summary/Discussion

The data from the human experiment shows that the hypothesis tested was true: a higher dosage of LPS (mg) leads to a significant rise in Inflammotin levels (pg/ml) in humans. The control showed very little Inflammotin (about 4 pg/ml) while each succeeding dosage rose Inflammotin levels significantly. The 15 mg dosage statistically showed a significant rise in Inflammotin levels (to around 660 pg/ml) in comparison to the control and previous, lesser dosages. The ANOVA test for the human study data showed that there was a statistical difference between the four groups. The six t-tests for the human study data then corrected for the error associated with multiple comparisons (Bonferroni Correction). These post-hoc tests each proved that there was a statistically significant difference within each of the four groups (0 mg, 5 mg, 10 mg, and 15 mg).

While the increasing LPS dosages made Inflammotin levels rise in humans, it did NOT statistically rise Inflammotin levels in rats. The t-test for rats proved not statistically significant between the 0 mg LPS dosage group and 10 mg LPS dosage grooup.

In conclusion, our results from this experiment proved that LPS did have an affect on Inflammotin level in humans but not in rats.

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