BME100 s2015:Group3 12pmL1

BME 100 Spring 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
OUR TEAM Name: Abraham Rosengard Name: Juan Patterson Name: Gabriella Leiva-Hidalgo Name: Your name Name: Your name Name: Your name LAB 1 WRITE-UP Independent and Dependent Variables Independent Variables: The independent variable is the concentration of the protein lipopolysaccharide. We will be starting with 10 mg and will reduce the dosage by 2.00 milligrams for each group until the dosage is down to 4 mg Dependent Variables: The dependent variable is the increase of the protein Inflammotin in the elderly. Experimental Design Groups There will be 4 groups. Age The test subjects would be from several retirement homes to account for randomization and will be focused around the age group of 65-75 years of age with relatively good health. Number of subjects per group There will be 10 people per group which reaches a total of 40 people. This would yield a good random distribution of participants and would be a fair amount to spend based on the lab’s current financial status. Ideally the groups would be consisted of both genders equally with varying nationalities. Subject Selection The test subjects would be from several retirement homes to account for randomization and will be focused around the age group of 65-75 years of age with relatively good health. To control this experiment we will be looking into the medical history of the participants for any pre-existing conditions. We would be particularly look into if any other medications taken have been known to interfere with either the independent or dependent variable, either increasing levels of Inflammotin. As well as any serious conditions in the past that could affect inflammotin production or the lipopolysaccharide that they will be ingesting. Sources of Error and Bias Potential sources error are interaction with other medication, diet, dietary conditions. Human error can also have drastic results like a tech prescribing the incorrect dose to a participant or entering the wrong information.