# BME100 f2015:Group14 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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## OUR TEAM## LAB 2 WRITE-UP## Descriptive Statistics
The average inflammotin level in pg/ml for the independent variable level of 0mg was: 3.834 The standard deviation was: 1.523 The standard error was: 0.482 The average inflammotin level in pg/ml for the independent variable level of 5mg was: 8.932 The standard deviation was: 1.594 The standard error was: 0.504 The average inflammotin level in pg/ml for the independent variable level of 10mg was: 61.622 The standard deviation was: 30.111 The standard error was: 9.522 The average inflammotin level in pg/ml for the independent variable level of 15mg was: 657.941 The standard deviation was: 212.943 The standard error was: 67.338 The count for this experiment was 10 (10 samples per dose)
Experiment 2 will be labeled as the experiment that consisted of a rat study. The average inflammotin level in pg/ml for the independent variable level of 0mg was: 10.516 The standard deviation was:2.226 The standard error was: 0.995 The average inflammotin level in pg/ml for the independent variable level of 10mg was: 11.112 The standard deviation was: 7.403 The standard error was: 3.311 The count for this experiment was 5 (5 samples per dose)
## Results
These results, being less than the alpha value 0.005, are all considered statistically significant.
Since there were only 2 levels of the independent variable utilized for the rat study, an ANOVA test was unnecessary and thus a T-test was performed instead. The p-value that resulted from this test was 0.867403497. This p-value was greater than the given value of alpha:0.05 and thus there was no statistical significance found within this data.
## Analysis
Analysis of the results beyond the graph are included in the section labeled results.
Analysis of the results beyond the graph are included in the section labeled results.
## Summary/DiscussionIn experiment one, it was determined through the use of an ANOVA test that there was overall statistical significance between the sets of data. Thus, it became necessary to then utilize a t-test to find whether or not there was statistical significance between the tests. This resulted in the production of p-values that showed statistical significance between all of the data sets for each level of the independent variable. In experiment two, it was determined through the use of a t-test (due to there being only 2 independent variable levels) that there was no statistical significance between the the two data sets for the levels of the independent variable. It is odd that in the rat study no statistical significance was found proving the lipopolysaccharide increased levels of LPS in the rats while the opposite was determined for the human study; however, this variation can possibly be explained by the lack of more independent levels and samples per dose of the independent level in the rat study. |