BME100 f2015:Group9 1030amL1

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Lab Write-Up 1 | Lab Write-Up 2 | Lab Write-Up 3
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OUR TEAM

Name: Glenna Bea Embrador
Name: Your name
Name: Your name
Name: Your name
Name: Your name
Name: Your name

LAB 1 WRITE-UP

Independent and Dependent Variables

Independent Variable: Dosage of lipopolysaccharide (mg)
Dependent Variable: Level of inflammation protein (Inflammotin)

The independent variable is the substance that we are manipulating in order to see how it effects the results (the dependent variable)

Experimental Design

Groups

We will have a total of 12 groups where half of the groups (groups 1-6) will be of ages 65-69, and the other half (groups 7-12) will be of ages 70-74

Each age group will then be subdivided by increments of 2 mg dosages: 2 mg, 4 mg, 6 mg, 8 mg, 10 mg, and a placebo


Age

Our age range will span from 65-74, split from ages 65-69 and ages 70-74 in order to get a better observation of how age plays a factor into the reaction of the lipopolysaccharide.


Number of subjects per group
10 subjects per group: 5 male, and 5 female in order to get a representative result of how lipopolysaccharide affects inflammotin levels.





Subject Selection

In order to create the groups, our team will go to a primary care physician near our area to get a list of patients who have had a history of inflammatory problems.
We will then use a random number generator to assign each patient to a specified group.
While conducting the experiment, we will hold a double blind experiment where neither the drug administer nor the patient knows what dosage the patient is receiving. After giving each patient their dosage of lipopolysaccharide, at the end of each day their Inflammotin levels will be recorded and at the end of the experiment we will compare the results to determine the lowest effective dosage of lipopolysaccharide.





Sources of Error and Bias

Because our subjects were taken from a local primary care physicians, the results may not be representative of how the lipopolysaccharide works for other patients worldwide. In addition, because we are taking patients will preexisting inflammatory conditions, other health issues may interfere with the accuracy of the results. Furthermore, some patients may not react at all to the medicine which may skew the results. Lastly, experimenter bias may occur where the scientist has preconceived expectations for the experiment and may inevitably guide the research towards a favorable result.