BME100 f2015:Group3 8amL1
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LAB 1 WRITE-UP
Independent and Dependent Variables
Independent Variables: Amount of LPS tested on subject / Male and Female
Dependent Variables: Change in protein levels
Total of 10 groups:
Starting with five groups of females ranging from 65-70 years old, we plan to test 9mg, on group one (a), 7mg. on group two (a), 5mg. on group three (a), 3mg. on group four (a), and 0mg. on group five (a) as our control group. We will also have five groups of males ranging from 65-70 and plan to use 9mg. on group one (b), 7mg. on group two (b), 5mg. on group three (b), 3mg. on group four (b), and 0mg. on group five (b) as our control group. After testing each effect of the drug on the test subjects in a each day over a three-day trial we will evaluate the results of the data and make appropriate adjustments.
We will run our experiment on males and females between the age of 65 and 70. This will allow us to have a more focused and controlled subject group while also keeping randomization in mind. We wanted to limit the variability due to limited funds. Choosing to separate gender was based on our hypothesis that each gender may be effected differently.
Each group will have 10 subjects. Choosing to test ten subjects per group was based on our need to have greater than seven subjects but not too broad of a subject group. Increasing the number of subjects seemed impractical based on our budget restrictions, but ten is thought to be a reliable number in receiving data.
Selecting our subjects will be based on age and gender. We will only test subjects between the ages of 65 and 70. Males and Females will be divided into different groups. The groups of males and females will each have 10 subjects that are randomly selected from our chosen age group. The age group 65-70 is the group with the highest population of ages considered elderly(65+) in America. Choosing the group with the highest population makes gathering subjects easier and serves as a strong representation of the elderly age group as a whole.
Sources of Error and Bias
Sources of error and biases: 1. Prior illnesses/ diseases- Heart disease, high blood pressure, diabetes, allergies etc. are all potential contributors to inflammation not caused by the medication. 2. Prior medications- Based on other medications the test subject was once on or is still on could create a tolerance to this new medication or a reverse reaction. 3. Genetics- Certain genetic markers could make the patient prone to previously mentioned illnesses and diseases or a higher resistance to the medication. 4. Ethnicity/ Race- Certain races are more vulnerable/ tolerable to specific diseases. 5. Environmental/ Geological- Based on temperature, humidity and region one subject may have been raised could effect how they react to the medication.