Specificity vs sensitivity
Fri, Sep 25, 2026 · Week 5 · Genetics of Disease (Medical Interventions)
Today's goal: Define sensitivity and specificity, sort supplied practice results into the four cells, compute both rates from the counts, and state what a classroom ELISA run cannot tell you about them.
This is a model of the work you should turn in today. Use it to check your own: match the structure and the level of detail, do not copy it. Your data and wording should be your own.
Read the supplied status first, then the supplied result.
- Has Infection Q and screen positive: true positive (TP, cell a).
- Has Infection Q and screen negative: false negative (FN, cell c).
- Does not have Infection Q and screen positive: false positive (FP, cell b).
- Does not have Infection Q and screen negative: true negative (TN, cell d).
The name of a cell is the result (positive or negative) plus whether the result was right (true or false).
Sensitivity counts the people with the condition who were caught; specificity counts the people without it who were cleared.
A screening result is never a confirmation; in the scenario, only the confirmatory test settles the question.
| Screen positive | Screen negative | |
|---|---|---|
| Has the condition (reference standard) | ||
| Does not have it (reference standard) |
This model shows the level of evidence and organization needed to complete: Parts A to E in one data table: definitions and layout, ten sorted practice rows with counts, two computed rates, the 1,000-person practice rates and positive column, and two limit sentences
- Name the variables and include units.
- Enter observations without changing the raw values.
- Check labels, calculations, and patterns before interpreting the data.
Keep the structure. Replace the question, facts, measurements, and evidence. Then recheck units, vocabulary, and whether the conclusion goes beyond the evidence.
Also due today: Keep this table with Tuesday's CER. Your next assigned lesson is set by your teacher. Do not assume any classroom ELISA result has been sorted into these cells; that would need a reference standard the run does not supply.
Turn in: Sensitivity and specificity data table
Go to Schoology to turn this in.
Submit one PDF. Schoology attaches your name to your upload; on the page itself, write your period and code. Name the file: FirstName LastName - Assignment Title - YYYY-MM-DD.pdf.
Open Schoology PDF upload helpIf you cannot get in, see Mr. Mendoza. Do not skip the work.
Claim ceiling: Every row and count is practice for the made-up Infection Q from Tuesday. No real disease, test or person. No classroom ELISA well, plate photo or lab result is used. Sensitivity counts the people with the condition who were caught; specificity counts the people without it who were cleared. Each needs a reference standard to be counted at all. A screening result is never a confirmation; in the scenario, only the confirmatory test settles the question. None of that supplies a reference standard for unknown samples, so a classroom run, by itself, cannot place its wells in the rows of this table or produce a sensitivity or specificity. This is your position about a practice scenario, not a rule and not medical advice.
One exam-style question that uses exactly what you practiced today. Try it before you reveal the answer, then read why each choice is right or wrong.
Tap an answer to see the full explanation. Nothing is recorded or graded.
It builds this reusable test skill: Distinguishing sensitivity from specificity.
- Name the concept or data pattern being tested.
- Cross out choices that violate that rule or the evidence.
- Justify the best remaining choice before checking the answer.