BME103 s2013:T900 Group5 L3: Difference between revisions
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| Sample Name || Ave. INTDEN* || Calculated μg/mL || Conclusion (pos/neg) | | Sample Name || Ave. INTDEN* || Calculated μg/mL || Conclusion (pos/neg) | ||
|- | |- | ||
| Positive Control || 5725984 || --- || N/A | | Positive Control || 5725984.00 || --- || N/A | ||
|- | |- | ||
| Negative Control || 2820659.67 || ---|| N/A | | Negative Control || 2820659.67 || ---|| N/A | ||
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| Tube Label: 1 Patient ID: 92336 rep 1 || 4902761.33 || --- || pos | | Tube Label: 1 Patient ID: 92336 rep 1 || 4902761.33 || --- || pos | ||
|- | |- | ||
| Tube Label: 2 Patient ID: 92336 rep 2 || 4957051 || --- || pos | | Tube Label: 2 Patient ID: 92336 rep 2 || 4957051.00 || --- || pos | ||
|- | |- | ||
| Tube Label: 3 Patient ID: 92336 rep 3 || 5446934.67 || --- || pos | | Tube Label: 3 Patient ID: 92336 rep 3 || 5446934.67 || --- || pos | ||
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| Tube Label: 5 Patient ID: 44606 rep 2 || 2202675.67 || --- || neg | | Tube Label: 5 Patient ID: 44606 rep 2 || 2202675.67 || --- || neg | ||
|- | |- | ||
| Tube Label: 6 Patient ID: 44606 rep 3 || 1789569 || --- || neg | | Tube Label: 6 Patient ID: 44606 rep 3 || 1789569.00 || --- || neg | ||
|} | |} | ||
<nowiki>* Ave. INTDEN = Average of ImageJ integrated density values from three Fluorimeter images</nowiki> | <nowiki>* Ave. INTDEN = Average of ImageJ integrated density values from three Fluorimeter images</nowiki> |
Revision as of 20:32, 15 April 2013
BME 103 Spring 2013 | Home People Lab Write-Up 1 Lab Write-Up 2 Lab Write-Up 3 Course Logistics For Instructors Photos Wiki Editing Help | |||||||||||||||||||||||||||||||||||||||||
OUR TEAMLAB 3 WRITE-UPOriginal System: PCR ResultsPCR Test Results
* Ave. INTDEN = Average of ImageJ integrated density values from three Fluorimeter images
Bayes Theorem is an equation in probability theory and statistics that relates inverse representations of probabilities concerning two events, or rather, it expresses a degree of change when accounting for evidence. Bayes Theorem is represented as follows: P(A|B) = P(B|A) * P(A) / P(B) Which can be read as the probability of A given B = (the probability of B given A * the probability of A) / the probability of B This information will be utilized to determine various probabilities listed below when accounting for the positive/negative values determined by the entire class as well as an outside document listing the actual yes/no cancer diagnosis
New System: Design StrategyWe concluded that a good system Must Have:
New System: Machine/ Device EngineeringSYSTEM DESIGN
KEY FEATURES We chose to include these new features
[OR] We chose keep the devices the same as the original system
INSTRUCTIONS
New System: ProtocolsDESIGN We chose to include these new approaches/ features
[OR] We chose keep the protocols the same as the original system
PROTOCOLS
New System: Research and DevelopmentBACKGROUND
DESIGN
New System: Software[THIS SECTION IS OPTIONAL. If your team has creative ideas for new software, and new software is a key component included in your new protocols, R&D, or machine design, you may describe it here. You will not receive bonus points, but a solid effort may raise your overall page layout points. If you decide not to propose new software, please delete this entire section, including the ==New System: Software== header.]
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