Genetics of Disease (Medical Interventions)
Unit 1: Unit 1.1 ELISA Lab & ControlsMI 1.1Biotechnology Research and Experiments

Evaluate False Positive Negative Risk

Use molecular-test evidence to evaluate false positive/negative risk accurately.

Builds on (2 levels back)inferred · high confidence
  • Control logic: Molecular results need positive and negative controls.
  • Signal interpretation: Bands, colors, curves, and E-values must be compared to a rule.

Prerequisites are inferred: pending teacher review.

Re-learn the skill with worked practice and clear examples.

Use a 2x2 table to weigh a false positive against a false negative and pick the error to avoid most.

Step 1: Read the 2x2 table
Rows are what the test said; columns are the true status. Off-diagonal boxes are the errors.
Test resultTruly infectedTruly healthy
Test says POSITIVE90 (true positive)8 (false positive)
Test says NEGATIVE10 (false negative)92 (true negative)
Two-by-two table of test results versus true status: 90 true positives, 8 false positives, 10 false negatives, 92 true negatives.
Step 2: Ask which error is worse here
For a first SCREENING test, a missed case (false negative) is usually the worst outcome, so you want to catch every real case.
Step 3: Name the limit
A screen that catches everyone will also flag some healthy people; those people still need a confirmatory test before any treatment.
Practice

A clinic uses a first SCREENING test for a serious, treatable infection. Why do they design the screen to avoid false negatives even if it raises false positives?

Reviewed
Test resultTruly infectedTruly healthy
Test says POSITIVE90 (true positive)8 (false positive)
Test says NEGATIVE10 (false negative)92 (true negative)
Two-by-two table of test results versus true status: 90 true positives, 8 false positives, 10 false negatives, 92 true negatives.
  1. A.A false negative would tell an infected person they are clear, so the disease goes untreated and can spread
  2. B.A false positive is always more dangerous than a false negative
  3. C.Screening tests are not allowed to make any errors
  4. D.Avoiding false negatives makes the test cheaper
Show the worked solution ▾

Answer: A. A false negative would tell an infected person they are clear, so the disease goes untreated and can spread

  1. Step 1: Spot the goal of a screen: A screen should not miss real cases.
  2. Step 2: Trace the harm: Missing a case = an infected person believes they are clear and gets no treatment.

Why it's right: Missing a real case (false negative) leaves an infectious, treatable disease untreated, so a screen is built to avoid that error first.

Why the others miss:
  • B: Which error is worse depends on the situation, not a fixed rule.
  • C: Every real test makes some errors; the goal is to choose which error to minimize.
  • D: Cost is not the reason; the reason is patient and public-health harm.

Aligned to Biotechnology Research and Experiments · reading level ~grade 9

Where you'd see this
  • In Unit 1.1 ELISA Lab & Controls, this skill turns class evidence into a result another person can check.
Video library
Watch: Evaluate False Positive Negative Risk
Positive & Negative Predictive Value (PPV & NPV) Explained
NurseKillam · ~11 min
Guided notes

Fill these in as you work through the lesson.

Big idea: Every test can make two kinds of mistakes, and you choose which mistake to avoid based on what the result will be used for.
Key terms: write the meaning
  • False positive (the test says ____ when the person is really healthy):  
  • False negative (the test says ____ when the person is really sick):  
  • Screening test (the first, wide test used to ____ as many real cases as possible):  
  • Confirmatory test (the second test that must be ____ before treatment starts):  
The rule

A screening test should avoid   negatives so it does not miss a case, and a confirmatory test should avoid   positives so it does not treat a healthy person.

Check yourself
  1. Which box in the 2x2 table is a false positive, and which is a false negative? 
  2. For a first screen of a treatable infection, which error is worse and why? 
  3. Why does a confirmatory test flip which error matters most? 
Work one example

A screen flags 8 healthy people and misses 0 sick people. Decide whether that trade-off is acceptable for a first screen, then say what those 8 people need next.