Antiviral data CER analysis
Open your materials, follow the steps, then turn in your work.
Analyze plaque-assay data and write a CER about antiviral effectiveness.
1. Open your materials
Use the materials named in the first step below. Open lesson resources.
2. Start the work
Graph plaque counts across treatment conditions.
Show all 5 required steps
- Graph plaque counts across treatment conditions.
- Make a claim about which antiviral was most effective.
- Cite two data points as evidence.
- Add reasoning connecting plaque count to viral inhibition.
- Note one limitation of the assay.
Lost your place? Reopen today's Antiviral data CER analysis record. Find the last completed evidence ID, check it against the claim ceiling, and continue with the first unfinished step rather than restarting the whole task.
Check your work before submitting
- CER includes claim, evidence, and reasoning.
- Reasoning links lower plaque counts to inhibition.
3. Turn in your work
DueCheck Schoology- Hand in
- Written CER analyzing plaque-assay data: claim naming the most effective antiviral, two specific plaque-count evidence entries with percent reduction, reasoning linking lower count to viral inhibition, and one limitation of the assay.
How to submit and name your file
Use the submission route shown on today's today's page.
In Schoology, open your course and the assignment for this lesson. Attach your file, select Submit, and check that it appears in the submission.
PDF upload helpYou get two school days for every day you were absent, so this deadline moves with you.
Choose your Schoology section. Open only one assignment.
Check the section number beside Human Anatomy and Physiology in Schoology.
Assignment: Wk17 CER: Antiviral data CER analysis
Link will not open? Open Schoology, choose your section, and find the assignment title above.
How this lesson connects
Keep using what you learned last class: A plaque assay estimates infectious virus under defined culture conditions, while eye dissection reveals structure; the two evidence types answer different questions and must not be treated as interchangeable. Today: A plaque assay estimates infectious virus from plaques formed under defined culture and dilution conditions, so antiviral comparisons require controls, countable dilutions, and a stated calculation rule.
Unit 3 guide: what to keep and use nextOptional: listen or watch a unit review▸
Need help? Warm-up, timing, and directions▸
💡 Big idea: A estimates infectious virus from plaques formed under defined and dilution conditions, so comparisons require controls, countable dilutions, and a stated calculation rule.
- 0-12Graph plaque counts per condition; label axes, title, error bars if applicable
- 12-28Identify the most effective from the graph; calculate percent reduction
- 28-48Write full CER: claim naming best , two plaque-count evidence entries, reasoning linking count to mechanism
- 48-60Add limitations section: at least one real limitation explained
- 60-72: check that reasoning explains the mechanism, not just restates counts
- 72-80Revise and submit CER
- • Your plaque-count from yesterday is the raw material for today's scientific argument.
- • Graphing the counts first makes the pattern visible before you write your claim.
- • The reasoning step is where you explain the mechanism: why does fewer plaques mean better ?
- • A limitations section makes your argument scientifically credible, not just optimistic.
- • A lower plaque count in a treated condition compared to the control indicates the reduced viral replication or spread.
- • Percent reduction is calculated as: (control count minus treated count) divided by control count, times 100.
- • Limitations of plaque assays include cell-line variability, observer counting error, and in-vitro vs. in-vivo differences.
PLTW connection and today's work
Complete the antiviral data-analysis or CER reflection prompt in Activity 3.2.3 Going Un-Viral (Lesson 3.2 Body Guards) on myPLTW; finish it before peer review of your plaque-assay CER.
Today's stopping point: Lab task is done; today the analysis task should show complete and your CER should be submitted.
PLTW activity titles identify the course connection. If your account will not open, use the posted materials for today and tell Mr. Mendoza. Do not mark an online activity complete unless you completed it.
Course connection
- Activity 3.2.3 Going Un-Viral
Use the turn-in directions at the top of this page. Do not create a second submission unless your teacher asks for one.
Show another explanation or a smaller first step
Need help? Choose a starting point
Lesson resources: reading, slides, and vocabulary▸
The deck carries the prior idea forward, lets you inspect an analogy, maps the rule to biology, and ends with the same evidence decision and exit ticket used on this page.
Generated from this lesson's canonical data with a red-team citation check.
A estimates infectious virus under defined conditions, while eye dissection reveals structure; the two evidence types answer different questions and must not be treated as interchangeable.
A estimates infectious virus from plaques formed under defined and dilution conditions, so comparisons require controls, countable dilutions, and a stated calculation rule.
A research team lays out its question, variables, controls, sampling plan, measurement record, and analysis before deciding what the data support.
- Which variable is changed or compared?
- Which conditions and measurements must stay consistent?
- Which conclusion is inside the study's evidence boundary?
Define variables, controls, sampling, units, and the analysis plan before interpreting a result; analysis cannot repair biased or inconsistent measurement.
A well-organized classroom study can still be limited by , measurement quality, confounding, and the population represented.
- • Question and variable cards map to the study design.
- • Control and measurement cards map to fair, reproducible data collection.
- • The conclusion card maps to a bounded claim supported by the analysis.
Driving question: Analyze plaque- data and write a CER about effectiveness.
What you already know: A estimates infectious virus under defined conditions, while eye dissection reveals structure; the two evidence types answer different questions and must not be treated as interchangeable.
New idea: A estimates infectious virus from plaques formed under defined and dilution conditions, so comparisons require controls, countable dilutions, and a stated calculation rule.
Visual or model: F1. F1. A lesson illustration or teaching diagram for Antiviral data CER analysis. Use it with E1-E3; it is a model or context image, not experimental or patient data. What to notice: Trace the labeled structure, movement, or system relationship that connects form to function.
- Observe or measure the relevant feature in data CER analysis.
- Organize the observation with a stable evidence ID.
- Apply this rule: Define variables, controls, sampling, units, and the analysis plan before interpreting a result; analysis cannot repair biased or inconsistent measurement.
- Choose the option the evidence supports and state the limit of the conclusion.
Real biomedical example: Today the human body systems team uses data CER analysis to make a bounded evidence decision. Plaque counts depend on susceptible cells, dilution, volume, technique, and viruses that form countable plaques; one classroom comparison does not establish clinical effectiveness.
What the evidence supports: E1-E3 and F1 support the daily take-home when the response meets the stated success criteria.
What it cannot prove: The package does not support claims beyond this lesson's or any real patient diagnosis.
- • : A lab method that counts infectious viruses by the clear spots they leave where they destroy cells in a layered dish.
- • : A type of medicine that fights viral infections by blocking a virus from entering cells or copying itself, rather than killing the virus outright.
- • : A microorganism such as a bacterium, virus, fungus, or parasite that can cause disease in its host.
- • : The passing of a disease-causing agent from one host to another, by routes such as contact, droplets, contaminated objects, or vectors.
- • titer: Use the lesson context and glossary entry to explain titer in your own words.
- • : Planned actions taken to reduce the chance of harm or to lessen its impact if it does happen.
Use it now: Choose one decision option. Cite E1 and E3, then explain how the rule connects the evidence to your choice.
Go further, optional: The source links below are optional enrichment. Every fact required for today's local evidence decision appears in this lesson package.
National Library of Medicine is the source this lesson's claim is checked against: Viral
Limit: Plaque counts depend on susceptible cells, dilution, volume, technique, and viruses that form countable plaques; one classroom comparison does not establish clinical effectiveness.
Define variables, controls, sampling, units, and the analysis plan before interpreting a result; analysis cannot repair biased or inconsistent measurement.
Limit: A well-organized classroom study can still be limited by , measurement quality, confounding, and the population represented.
CER includes claim, evidence, and reasoning.
Limit: E3 defines the classroom product or success criterion. It is not independent scientific evidence and cannot justify a clinical or causal claim.
PLTW-HAP-2027-05-10 · Simulated classroom evidence scenario
Your role: anatomy and physiology consultant
Decision: Your team must decide what the evidence from data CER analysis supports before submitting the claim-evidence-reasoning response named on today's page.
- • Write that the drug works for patients, because your polished CER shows far fewer plaques than the untreated plate.
- • Hold the CER until clinical outcome data arrives, because one classroom comparison cannot establish effectiveness in patients.
- • Claim the lowered plaque counts under our conditions, naming your control, countable dilution, and calculation rule.
Response: State one choice, cite at least two evidence IDs, explain the rule that connects them, and add one limitation. Submit it as the claim-evidence-reasoning response.
Claim ceiling: Today's evidence supports a classroom claim about data CER analysis. It cannot prove causation, diagnose a real patient, or justify action outside this room.
Reason for review: Your team must decide what the evidence from data CER analysis supports before submitting the claim-evidence-reasoning response named on today's page.
Context: Today the human body systems team uses data CER analysis to make a bounded evidence decision. Plaque counts depend on susceptible cells, dilution, volume, technique, and viruses that form countable plaques; one classroom comparison does not establish clinical effectiveness.
- • T1: Graph plaque counts across treatment conditions.
- • T2: Make a claim about which was most effective.
- • T3: Cite two data points as evidence.
- • T4: Add reasoning connecting plaque count to viral .
- • T5: Note one limitation of the .
- • E1: National Library of Medicine is the source this lesson's claim is checked against: Viral
- • E2: Define variables, controls, sampling, units, and the analysis plan before interpreting a result; analysis cannot repair biased or inconsistent measurement.
- • E3: CER includes claim, evidence, and reasoning.
Measurements: Use only the measurements, units, graph, or counts supplied in today's task. No additional patient measurement is implied.
Figure finding: Teaching diagram for data CER analysis. Trace the labeled structure, movement, or system relationship that connects form to function. This is a teaching model, not patient or experimental data.
Uncertainty: This is a composite classroom scenario. Missing history, measurements, or confirmation tests remain unknown and limit the conclusion.
= final volume / sample volume. New concentration = starting concentration / dilution factor.
Mix 1 mL of sample to a final volume of 10 mL. The is 10. A 100 mg/mL starting sample becomes 10 mg/mL.
Use the same volume units before dividing. Concentration keeps its original concentration unit.
Apply the same setup to one supplied dilution or dose. Show the factor, new value, units, and a reasonableness check.
Students often think A polished answer about data CER analysis is trustworthy even when its evidence source, comparison, or limitation is missing.. The trap: Presentation quality cannot raise the evidence level. Plaque counts depend on susceptible cells, dilution, volume, technique, and viruses that form countable plaques; one classroom comparison does not establish clinical effectiveness.
1. Decision or claim I am testing: ____
2. Evidence ID and exact observation: ____
3. Second evidence ID and exact observation: ____
4. Rule that connects the evidence to my claim: ____
5. Strongest alternative or tradeoff: ____
6. Limitation or missing evidence that controls my confidence: ____
7. Revision I would make if the missing evidence changed: ____
This model shows the level of evidence and organization needed to complete: A blank structure for organizing the assigned response. It contains no claim, ranking, calculation, data interpretation, or recommendation from today's task.
- Write one defensible claim.
- Choose specific evidence that supports the claim.
- Explain the scientific rule that connects the evidence to the claim.
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: Submit your antiviral CER on Schoology.
- CER:
- Claim, Evidence, Reasoning: make a claim, back it with evidence, explain your reasoning.
- SOP:
- Standard Operating Procedure, the exact steps to follow (especially in a lab).
- Tracker:
- Your PLTW progress log where you record completed evidence.
- myPLTW:
- The PLTW course site where you do the online activities. Find it in Clever with your Microsoft sign-in, right next to Schoology.
Tap the speaker to hear a term. Add two of these to your notebook glossary with a definition and an example in your own words.
Pick just 2 or 3 words from today and make them yours: write what each one means in your own words, name the context clue or evidence that helped, then give one example from what you actually did in Antiviral data CER analysis. Try your own words first; the glossary is there if you get stuck. This is voluntary and counts as extra credit, so keep it short.
Saved on this device. Show Mr. Mendoza or add these to your notebook glossary to claim the extra credit.
A fillable, Cornell-style notebook for Unit 3: Adventure Awaits. Type your notes, cues, and summaries right in the PDF, or print it and write by hand. Each lesson page has a cue column, a notes column, and a summary box, plus dated lab-record pages you can turn in.
HBS Unit 3 notebook: Adventure Awaits Fillable PDFCornell notes + lab recordsOpenVetted readings and references for this unit. Use them to prepare, to catch up if you were absent, or to go deeper on today's target.
Practice: try a question, then check your answer▸
Claim ceiling for this check: Today's evidence supports a classroom claim about data CER analysis. It cannot prove causation, diagnose a real patient, or justify action outside this room.
A student makes a certain conclusion about Antiviral data CER analysis from one classroom result. What must the student add before the conclusion is defensible?
Write an answer and pick a confidence to unlock the key.
Fast retrieval with instant answers, not the commit-then-reveal check above. Try each from memory first: write what you remember about the earlier units, then check yourself here.
Missed class or ready for more?▸
Run this before you touch the bench. It is built from the real lab procedure, so the decisions you make here are the ones you will make with the equipment in your hands. This lesson has more than one, and they cover different skills.
What today's skills lead to. These are real health-science careers this course builds toward. Tap one to see, on the US Department of Labor's O*NET site, what the job actually involves, what it pays, and how fast it is growing.
The bench work needs equipment you do not have at home. Do the thinking half now: read the procedure, write your prediction, and set up your data table so it is ready.
Back in class. Ask Mr. Mendoza for the class data set, or for a bench slot to run it yourself. Do not submit a CER with invented numbers.
Class still runs. Complete the online activity above (it's self-guided). Need the concept taught without a teacher? Use this authoritative explainer:
CDC: Travelers' HealthYou've passed Unit 2, so the optional extra-credit track is open. Complete reserved-unit work from home, including virtual labs, for extra credit. Each item shows its correct submission route.
Open the extra-credit track- CompleteEvery required part of the artifact is present, nothing left blank.
- AccurateThe science and the data are correct and match the evidence.
- Scientific reasoningYou explain your claim with evidence and reasoning (CER), not just an answer.
- Professional communicationClear, organized, labeled, and written the way a clinician or scientist would.
- SubmittedGo to Schoology to turn this in. Submit one PDF. Put your first and last name in the document header. Name the file: FirstName LastName - Assignment Title - YYYY-MM-DD.pdf. If you cannot get in, see Mr. Mendoza. Do not skip the work.
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