# BME103 s2013:TEMPwu3

(Difference between revisions)
 Revision as of 17:57, 9 April 2013 (view source) (→Original System: PCR Results)← Previous diff Revision as of 18:07, 9 April 2013 (view source) (→Original System: PCR Results)Next diff → Line 49: Line 49: '''Bayesian Statistics'''
'''Bayesian Statistics'''
+ These statistics are based upon all of the DNA detection system results for 34 hypothetical patients who were diagnosed as either having cancer or not having cancer.
+ Bayes Theorem equation: P(A|B) = P(B|A) * P(A) / P(B) Bayes Theorem equation: P(A|B) = P(B|A) * P(A) / P(B) - Calculation 1: The probability that the sample actually has the cancer DNA sequence, given a positive diagnostic signal, or P(A|B).
+ + Calculation 1: The probability that the sample actually has the cancer DNA sequence, given a positive diagnostic signal.
+ * A = [text description] = [frequency shown as a fraction] = [final numerical value] + * B = [text description] = [frequency shown as a fraction] = [final numerical value] + * P (B|A) = [text description] = [frequency shown as a fraction] = [final numerical value] + * '''P(A|B) = [answer]''' +
+ + + Calculation 2: The probability that the sample actually has a non-cancer DNA sequence, given a negative diagnostic signal.
+ * A = [text description] = [frequency shown as a fraction] = [final numerical value] + * B = [text description] = [frequency shown as a fraction] = [final numerical value] + * P (B|A) = [text description] = [frequency shown as a fraction] = [final numerical value] + * '''P(A|B) = [answer]''' +
+ + Calculation 3: The probability that the sample actually has a non-cancer DNA sequence, given a negative diagnostic signal.
* A = [text description] = [frequency shown as a fraction] = [final numerical value] * A = [text description] = [frequency shown as a fraction] = [final numerical value] * B = [text description] = [frequency shown as a fraction] = [final numerical value] * B = [text description] = [frequency shown as a fraction] = [final numerical value]

## Revision as of 18:07, 9 April 2013

BME 103 Spring 2013 Home
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Lab Write-Up 1
Lab Write-Up 2
Lab Write-Up 3
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# OUR TEAM

 Name: StudentRole(s) Name: StudentRole(s) Name: StudentRole(s) Name: StudentRole(s) Name: StudentRole(s)

# LAB 2 WRITE-UP

## Original System: PCR Results

PCR Test Results

 Sample Name ng/mL Conclusion (pos/neg) Positive Control --- N/A Negative Control --- N/A Tube Label:___ Patient ID: ____ rep 1 --- Tube Label:___ Patient ID: ____ rep 2 --- Tube Label:___ Patient ID: ____ rep 3 --- Tube Label:___ Patient ID: ____ rep 1 --- Tube Label:___ Patient ID: ____ rep 2 --- Tube Label:___ Patient ID: ____ rep 3 ---

Bayesian Statistics
These statistics are based upon all of the DNA detection system results for 34 hypothetical patients who were diagnosed as either having cancer or not having cancer.

Bayes Theorem equation: P(A|B) = P(B|A) * P(A) / P(B)

Calculation 1: The probability that the sample actually has the cancer DNA sequence, given a positive diagnostic signal.

• A = [text description] = [frequency shown as a fraction] = [final numerical value]
• B = [text description] = [frequency shown as a fraction] = [final numerical value]
• P (B|A) = [text description] = [frequency shown as a fraction] = [final numerical value]

Calculation 2: The probability that the sample actually has a non-cancer DNA sequence, given a negative diagnostic signal.

• A = [text description] = [frequency shown as a fraction] = [final numerical value]
• B = [text description] = [frequency shown as a fraction] = [final numerical value]
• P (B|A) = [text description] = [frequency shown as a fraction] = [final numerical value]

Calculation 3: The probability that the sample actually has a non-cancer DNA sequence, given a negative diagnostic signal.

• A = [text description] = [frequency shown as a fraction] = [final numerical value]
• B = [text description] = [frequency shown as a fraction] = [final numerical value]
• P (B|A) = [text description] = [frequency shown as a fraction] = [final numerical value]

## New System: Design Strategy

We concluded that a good system Must Have:

• [Must have #1 - why? short, ~4 or 5 sentences]
• [Must have #2 - why? short, ~4 or 5 sentences]

We concluded that we would Want a good system to have:

• [Want #1 - why? short, ~4 or 5 sentences]
• [Want #2 - why? short, ~4 or 5 sentences

We concluded that a good system Must Not Have:

• [Must Not Have #1 - why? short, ~4 or 5 sentences]
• [Must Not Have #2 - why? short, ~4 or 5 sentences]

We concluded that a good system Should Avoid:

• [Should Avoid #1 - why? short, ~4 or 5 sentences]
• [Should Avoid #2 - why? short, ~4 or 5 sentences]

## New System: Machine/ Device Engineering

DESIGN STRATEGY

We chose to include these new features

• Feature 1 - explanation of how this addresses any of the the Must Have/ Must Not Have items in the
• Feature 2 - description * Etc.

[OR]

We chose keep the devices the same as the original system
[Short paragraph explaining why the original system satisfies the design needs that you listed above]

DESIGN APPROACH

## Protocols

Materials

PCR Protocol

DNA Measurement Protocol

## Research and Development

Background on Disease Markers

Primer Design

Illustration