Genetics of Disease (Medical Interventions)

Unit 1: Unit 1.1 ELISA Lab & ControlsMI 1.1Biotechnology Research and Experiments

Distinguish Sensitivity vs Specificity

Use molecular-test evidence to distinguish sensitivity vs specificity 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 molecular-test evidence to distinguish sensitivity vs specificity accurately.

Step 1: Learn the key

Read the control [blank], compare the sample signal to the [blank], and report the result with one [blank].

Truth	Test result	Name
Has disease	positive	true positive
Has disease	negative	false negative
No disease	positive	false positive
No disease	negative	true negative

Step 2: Use the model

Read the figure, table, control, range, or protocol before choosing an answer.

Step 3: Name the limit

Say what the evidence can support and what it cannot prove yet.

Practice

Use the table. Looking only at the 100 truly HEALTHY people, what is the specificity of this test?

Reviewed

Group (n=100 each)	Test positive	Test negative
Truly INFECTED	95	5
Truly HEALTHY	5	95

A.95%
B.5%
C.50%
D.95 people

Show the worked solution ▾

Answer: A. 95%

Step 1: Pick the right row: Specificity uses the truly HEALTHY group only.
Step 2: Find correctly cleared: Of the 100 truly healthy, 95 test negative (correctly cleared).
Step 3: Divide: Specificity = 95 / 100 = 95%.

Why it's right: Specificity is the fraction of truly healthy people correctly cleared: 95 of 100 = 95%.

Why the others miss:

B: 5% is the fraction wrongly flagged positive (the false positive rate), not specificity.
C: 50% ignores the actual counts; 95 of 100 is 95%, not half.
D: Specificity is a percentage (a fraction), not a raw count of people.

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.

Careers that use this

Molecular Technologist: Uses distinguish sensitivity vs specificity to make a decision from evidence without overclaiming.

Video library

Watch: Distinguish Sensitivity vs Specificity

Sensitivity vs Specificity Explained Real Diagnostic Data ELISA, PCR

Bio-Resource · ~10 min

Guided notes

Fill these in as you work through the lesson.

Big idea: Sensitivity and specificity measure two different things: sensitivity is how well a test catches the truly positive, and specificity is how well it clears the truly negative.

Key terms: write the meaning

Sensitivity (of the truly positive, the fraction the test detects):
Specificity (of the truly negative, the fraction correctly cleared):
False positive (a healthy person the test wrongly flags positive):
False negative (an infected person the test wrongly clears):

The rule

Sensitivity = of the truly people, the fraction detected; specificity = of the truly people, the fraction correctly cleared.

Check yourself

If a test catches 95 of 100 truly infected people, which property is 95%?
From the truly healthy row, how do you compute specificity?
What kind of error is a healthy person flagged positive, and how does it relate to specificity?

Work one example

Of 100 truly infected, 95 test positive: sensitivity = 95/100 = 95%. Of 100 truly healthy, 95 test negative: specificity = 95/100 = 95%.