BME100 f2014:Group31 L2: Difference between revisions

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==Inferential Statistics==
==Inferential Statistics==

Revision as of 22:41, 15 September 2014

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OUR TEAM

Name: Jimmy Xu
Name: Andrew Liu
Name: Andy Chang
Name: Charles Bolton
Name: Afshin Isadvesta
Name: Michael Chatarachanwong

LAB 2 WRITE-UP

Descriptive Statistics

Experiment 1
Effect of LPS Dosage on Human Inflammotin Levels

0 mg: Mean-3.834, Std. Dev-1.52301018, Count-10, Std. Error-0.48161811

5 mg: Mean-8.932, Std. Dev-1.59393155, Count-10, Std. Error-0.50404541

10 mg: Mean-61.622, Std. Dev-30.1106939, Count-10, Std. Error-9.52183745

15 mg: Mean-657.941, Std. Dev-212.942976, Count-10, Std. Error-67.3384817


Experiment 2

0 mg: Mean-10.516, Std. Dev-2.22555162, Count-5, Std. Error-0.99529694

10 mg: Mean-11.112, Std. Dev-7.40288592, Count-5, Std. Error-3.31067123




Graphing

Experiment 1
In the first experiment tested on Humans, the conclusion can be lead that from 10 mg to 15 mg, there was a significant change of protein levels. In the first experiment tested on Rats, the conclusion can be lead that there is no significant change of LPS levels in rats corresponding to Protein intake.

Experiment 2



Inferential Statistics

Experiment 1

For the human experiment, an ANOVA test will be used, since there were four dosages that were tested, which is more than two.

Anova: Single Factor

Group: 5.23, Count: 9, Sum: 33.11, Average: 3.678888889, Variance: 2.338836111

Group: 10.72, Count: 9, Sum: 78.6, Average: 8.733333333, Variance: 2.414175

Group: 100.19, Count: 9, Sum: 516.03, Average: 57.33666667, Variance: 813.3897

Group: 793.17, Count: 9, Sum: 5786.24, Average: 642.9155556, Variance: 48472.95523

ANOVA Source of Variation

Between Groups, SS: 2607705.519, df: 3, MS: 869235.173, F: 70.53891752, P-Value: 3.39557E-14, F-crit: 2.90111958

Within Groups, SS: 394328.7835, df: 32, MS: 12322.77448

Total, SS: 3002034.302, df: 35

The P-Value obtained from the ANOVA single factor test was less than .05, which means that there is a statistically significant difference between treatments. A Bonferroni Post-Hoc Test was done, doing multiple t-tests between each dosage compared to all other dosages.

Post ANOVA T-Test

0mg v 5mg 8.59631E-07

0mg v 10mg 9.94377E-06

0mg v 15mg 1.39436E-08

5mg v 10mg 3.01859E-05

5mg v 15mg 1.57101E-08

10mg v 15mg 6.4824E-08


Because there are 6 possible t-tests to be done, the p value must be adjusted by dividing by number of tests. So the relevant threshold will be .05/6, which is .00833.

Based on the Post ANOVA t-tests, all p-values are less than .00833, which means that at every dosage, there was a statistically significant difference in inflammotin levels.


Experiment 2

For the rat experiment, a t-test will be used, since there are two dosages being tested. Furthermore, the data is among two unrelated sets of data, so it is clear that we need to use an unpaired test.

Unpaired T-Test: 0.8674035

For the unpaired t-test run on the rat experiment, the p-value was determined to be 0.8674035, which is greater than .05. Therefore, there is no statistical difference between the groups. Since there are only two variables, no adjustment of the p-level is needed.




Summary/Discussion

Based on these results, there was a significant difference in protein levels for all the human tests as dosage increased. On the other hand, there was no significant difference within the rat experiment as dosage increased. Therefore, we conclude that as LPS dosage increases, inflammotin levels rise in humans and only humans. In comparison, an increase in LPS levels in rats would create no statistically significant change in the levels of the same protein.