MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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**Table Explanation:**

The table represents the outcomes of an enzyme immunoassay screening test for HIV applied to a hypothetical population of 300 million Americans.

**Table Data:**

- **Have HIV:**
  - Test Positive: 1,339,370
  - Test Negative: 4,030
  - Total: 1,343,400

- **Do Not Have HIV:**
  - Test Positive: 4,479,849
  - Test Negative: 294,176,751
  - Total: 298,656,600

- **Overall Totals:**
  - Test Positive: 5,819,219
  - Test Negative: 294,180,781
  - Total: 300,000,000

**Questions and Analysis:**

a. **False Positives:**
   - There are 4,479,849 false positives (people who do not have HIV but tested positive). False positives can lead to anxiety, unnecessary further testing, and psychological distress for the person tested.

b. **False Negatives:**
   - There are 4,030 false negatives (people who have HIV but tested negative). False negatives can result in a lack of necessary treatment and care, potentially leading to the spread of the virus.

c. **Sensitivity:**
   - Sensitivity is calculated as the proportion of true positives (1,339,370) out of the total who have HIV (1,343,400). It measures the test's ability to correctly identify those with the disease.

d. **Specificity:**
   - Specificity is the proportion of true negatives (294,176,751) out of all those who do not have HIV (298,656,600). It measures the test's ability to correctly identify those without the disease.

e. **Positive Predictive Value (PPV):**
   - PPV is the probability that a person truly has HIV given that they tested positive. Use the formula: PPV = True Positives / Total Test Positives.

f. **Negative Predictive Value (NPV):**
   - NPV is the probability that a person truly does not have HIV given that they tested negative. Use the formula: NPV = True Negatives / Total Test Negatives.

g. **Reluctance for Universal Screening:**
   - Reluctance to recommend universal screening may be due to the high number of false positives,
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Transcribed Image Text:**Table Explanation:** The table represents the outcomes of an enzyme immunoassay screening test for HIV applied to a hypothetical population of 300 million Americans. **Table Data:** - **Have HIV:** - Test Positive: 1,339,370 - Test Negative: 4,030 - Total: 1,343,400 - **Do Not Have HIV:** - Test Positive: 4,479,849 - Test Negative: 294,176,751 - Total: 298,656,600 - **Overall Totals:** - Test Positive: 5,819,219 - Test Negative: 294,180,781 - Total: 300,000,000 **Questions and Analysis:** a. **False Positives:** - There are 4,479,849 false positives (people who do not have HIV but tested positive). False positives can lead to anxiety, unnecessary further testing, and psychological distress for the person tested. b. **False Negatives:** - There are 4,030 false negatives (people who have HIV but tested negative). False negatives can result in a lack of necessary treatment and care, potentially leading to the spread of the virus. c. **Sensitivity:** - Sensitivity is calculated as the proportion of true positives (1,339,370) out of the total who have HIV (1,343,400). It measures the test's ability to correctly identify those with the disease. d. **Specificity:** - Specificity is the proportion of true negatives (294,176,751) out of all those who do not have HIV (298,656,600). It measures the test's ability to correctly identify those without the disease. e. **Positive Predictive Value (PPV):** - PPV is the probability that a person truly has HIV given that they tested positive. Use the formula: PPV = True Positives / Total Test Positives. f. **Negative Predictive Value (NPV):** - NPV is the probability that a person truly does not have HIV given that they tested negative. Use the formula: NPV = True Negatives / Total Test Negatives. g. **Reluctance for Universal Screening:** - Reluctance to recommend universal screening may be due to the high number of false positives,
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