# BME100 f2015:Group3 1030amL2

BME 100 Fall 2015 | Home People Lab Write-Up 1 | Lab Write-Up 2 | Lab Write-Up 3 Lab Write-Up 4 | Lab Write-Up 5 | Lab Write-Up 6 Course Logistics For Instructors Photos Wiki Editing Help
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## Contents## OUR TEAM## LAB 2 WRITE-UP## Descriptive Statistics
## Results
_{Note: * (asterisk) indicates the t-test revealed that the dosage was less than the P-value, .00833,
thus indicating that there is over 95% confidence in the accuracy and credibility in the graph.}
*HUMAN LPS DOSAGE GRAPH DATA:_{Note: Significant figures not applied}
_{Note: No * (asterisk) indicates the t-test revealed that the dosage was greater than the P-value, .05,
thus indicating that there is less than 95% confidence in the accuracy and credibility in the graph.}
*RAT LPS DOSAGE GRAPH DATA:_{Note: Significant figures not applied}
## Analysis
The ANOVA test was selected to compare the significance between the dosage groups in the human study because more than 2 groups are being compared. The corrected p-value of the ANOVA test for the human study was 1.40083E-16 as shown above in blue, and because it was significantly lower than the alpha (α) p-value of 0.05, it indicates that there is a statistically significant difference among the LPS dosages and that further testing, i.e. ad-hoc test, must be done to determine the significance of the data.
The simple t-test was chosen to compare the two groups, 0mg and 10mg LPS dosage, in the rat study because there were only two groups to compare for significance, and there fore there was not a need for the ANOVA test. The α p-value remains unchanged at 0.05 because there was no ANOVA test required to correct the p-value. Between the 0mg and 10mg groups, their t-test value was calculated to be 0.867403497, which is noticeably higher than the p-value; this indicates that there shows to be no statistical significance in this set of data.
## Summary/Discussion
The goal of this study is to prove that there is a relationship between the dosage amount of the drug and the inflammotin levels in the human subjects. Each subject was given a dosage of 0mg, 5mg, 10mg, and 15mg. The results shown indicate their inflammotin levels after taking the drug. The mean was calculated to show the average level of inflammotin in each subject at the different dosage amounts and the standard deviation shows the variation of the results in the data set. The standard error shows the standard deviation of the mean of the data set results. The graph shown above depicts each data set and its error bars, which show the group variance. After the results were calculated, the ANOVA test was used to find the p-value, showing the percent confidence in the results. The p-value came out to be less than 0.05, indicating that t-tests are necessary to more accurately show the significance of the study. Each of the tests in this experiment show significance among the data.
The goal of this study is to prove that there is a relationship between the dosage amount of the drug and the inflammotin levels in the rats. Each of the ten subjects was given a dosage of 0mg or 10mg; 5 rats on 0mg and 5 on 10mg. The results showed each rat’s inflammotin level after taking the drug. The mean was calculated to show the average level of inflammotin in each subject at the different dosage levels and the standard deviation shows the variation of the results in the data set. The standard error shows the standard deviation of the mean of the data set results. The graph shown above depicts each data set and its error bars, which show the group variance. After the results were calculated, a t-test was used to find if the results were significant. The t-test value was found to be greater than 0.05 and therefore is not significant.
Despite that both experiments used the same lipopolysaccharide drug, there remained huge differences among the two studies. For one, the human study revealed that all the collected data had significance, while in the rat study, the t-test revealed that there was no significance between the 0mg and 10mg rat groups. Even in the human ad-hoc test comparison with 0mg vs.
10mg, there showed to still be a statistical significance, which is the opposite of the rat comparison. This goes to show that despite similar drug dosages, the effects of certain drugs could react differently in different organisms. The rat data in the section |