CER paragraph
Open your materials, follow the steps, then turn in your work.
Write a claim-evidence-reasoning paragraph and distinguish correlation from causation in your data.
1. Open your materials
Use the materials named in the first step below. Open lesson resources.
2. Start the work
Write down the estimate you read off the class line for the coded unknown, then take the true concentration Mr. Mendoza reveals and record how far off you were.
Show all 6 required steps
- Write down the estimate you read off the class line for the coded unknown, then take the true concentration Mr. Mendoza reveals and record how far off you were.
- State a claim your graph supports.
- Cite specific evidence from the data table or graph.
- Explain the reasoning linking evidence to claim.
- Decide whether your data shows correlation or causation and justify it.
- Note one alternative explanation for the pattern, and say whether your miss on the unknown is bigger or smaller than the width of one dilution step.
Lost your place? Interrupted? Reread your claim (step 1). If you have specific numbers cited from your table under it (step 2), move to step 3 and write your reasoning. If your claim is still vague, tighten it first.
Check your work before submitting
- Your paragraph includes a claim, evidence, and reasoning.
- You correctly labeled the relationship as correlation or causation.
- You compared your estimate for the unknown against its true value and judged the size of the miss.
3. Turn in your work
DueCheck Schoology- Hand in
- CER paragraph with a specific claim supported by cited graph data, reasoning linking evidence to claim, a correlation/causation classification with justification, and one alternative explanation.
How to submit and name your file
Use the submission route shown on 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.
How this lesson connects
Keep using what you learned last class: The axis, unit, and outlier decisions you bake into a graph control what a reader concludes, so a rushed graph can broadcast a claim your data never actually supported. Today: A CER paragraph converts a graph into an argument because it forces you to name the exact number and the exact reasoning, so a reader can check your logic instead of trusting your impression.
Optional: listen or watch a unit review▸
Need help? Warm-up, timing, and directions▸
💡 Big idea: A CER paragraph converts a graph into an argument because it forces you to name the exact number and the exact reasoning, so a reader can check your logic instead of trusting your impression.
- 0-10 minThe reveal: record your estimate for the coded unknown, take its true concentration, and write down how far off the class line was
- 10-20 minDraft your claim sentence; identify specific evidence values from the graph
- 20-40 minWrite the reasoning connecting evidence to claim
- 40-55 minClassify the relationship as correlation or causation with written justification
- 55-70 minAdd one alternative explanation for the observed pattern
- 70-80 min: does the CER hold together without looking at the graph?
- • Your graph is a picture, but a CER paragraph is the argument that makes it mean something.
- • Today we use your graph to write a claim, back it with specific data, and reason through it.
- • Then we'll ask the harder question: does your graph show that one thing caused another, or just that they moved together?
- • One honest alternative explanation makes your argument stronger, not weaker.
- • A claim is a specific statement the data supports, not a vague observation.
- • Evidence in a CER must come from actual data values, not general impressions.
- • Correlation and causation are logically distinct; environmental data almost always shows correlation.
PLTW connection and today's work
Open Problem 4 in your myPLTW course shell and navigate to the current activity, then write a CER paragraph using your graph data and classify the relationship as correlation or causation.
Today's stopping point: The graph draft is done; CER writing is the analysis milestone, so check your activity guide and submit the paragraph today.
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 4.1.3 Testing the Waters
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.
The axis, unit, and outlier decisions you bake into a graph control what a reader concludes, so a rushed graph can broadcast a claim your data never actually supported.
A CER paragraph converts a graph into an argument because it forces you to name the exact number and the exact reasoning, so a reader can check your logic instead of trusting your impression.
An engineering team tests one prototype feature at a time against a written criterion and records each failure before revising.
- Which criterion is being tested?
- What stays controlled between trials?
- Which result justifies a specific revision?
A useful prototype test links a controlled trial to a measurable criterion and turns the result into a documented revision decision.
A classroom test can reveal a design weakness without establishing clinical , effectiveness, durability, or regulatory readiness.
- • The written criterion maps to the pass condition.
- • Repeated controlled trials map to test evidence.
- • The revision log maps to the next design change and its rationale.
Driving question: Your graph shows two things rising together in your environmental data. What is the exact claim your numbers support, and can you honestly say one caused the other?
What you already know: The axis, unit, and outlier decisions you bake into a graph control what a reader concludes, so a rushed graph can broadcast a claim your data never actually supported.
New idea: A CER paragraph converts a graph into an argument because it forces you to name the exact number and the exact reasoning, so a reader can check your logic instead of trusting your impression.
Visual or model: F1. F1. A lesson illustration or teaching diagram for CER paragraph. Use it with E1-E3; it is a model or context image, not experimental or patient data. What to notice: Trace the labeled system, test, or design relationship and identify which evidence should trigger revision.
- Observe or measure the relevant feature in CER paragraph.
- Organize the observation with a stable evidence ID.
- Apply this rule: A useful prototype test links a controlled trial to a measurable criterion and turns the result into a documented revision decision.
- Choose the option the evidence supports and state the limit of the conclusion.
Real biomedical example: Your graph shows two things rising together in your environmental data. What is the exact claim your numbers support, and can you honestly say one caused the other?
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.
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.
A planned study connects its question to defined variables, controls, sampling, measurement, and analysis so the resulting data can support a bounded and reproducible conclusion.
Limit: A statistical difference or trend does not automatically establish practical importance, causation, generalizability, or freedom from bias.
A useful prototype test links a controlled trial to a measurable criterion and turns the result into a documented revision decision.
Limit: A classroom test can reveal a design weakness without establishing clinical , effectiveness, durability, or regulatory readiness.
Your paragraph includes a 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-BFH-2027-04-15 · Simulated classroom evidence scenario
Your role: biomedical design team member
Decision: Your team must decide what the evidence from CER paragraph supports before submitting the claim-evidence-reasoning response named on today's page.
- • State that the two variables rise together, cite the exact number from your graph, and explain why it supports that claim.
- • Write that the first variable caused the second, because the two lines climb together so tightly on your graph.
- • Look for a third factor driving both variables before writing the claim, since your data cannot rule one out yet.
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 CER paragraph. 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 CER paragraph supports before submitting the claim-evidence-reasoning response named on today's page.
Context: Evidence and reasoning are separate jobs: evidence is the specific number you point to, reasoning is why that number supports your claim, and confusing correlation for causation is the fastest way to lose an argument you could have won.
- • T1: Write down the estimate you read off the class line for the coded unknown, then take the true concentration Mr. Mendoza reveals and record how far off you were.
- • T2: State a claim your graph supports.
- • T3: Cite specific evidence from the or graph.
- • T4: Explain the reasoning linking evidence to claim.
- • T5: Decide whether your data shows correlation or causation and justify it.
- • T6: Note one alternative explanation for the pattern, and say whether your miss on the unknown is bigger or smaller than the width of one dilution step.
- • E1: A planned study connects its question to defined variables, controls, sampling, measurement, and analysis so the resulting data can support a bounded and reproducible conclusion.
- • E2: A useful prototype test links a controlled trial to a measurable criterion and turns the result into a documented revision decision.
- • E3: Your paragraph includes a 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 CER paragraph. Trace the labeled system, test, or design relationship and identify which evidence should trigger revision. 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.
- • The solution must address the stated need in CER paragraph.
- • The decision must be supported by E1-E3.
- • The final product must make the success criteria visible.
- • Complete the work inside the 80-minute block.
- • Use only supplied or teacher-approved materials and evidence.
- • Do not trade , accessibility, or privacy for speed.
- • and evidence quality: must pass before scoring other criteria.
- • User need and effectiveness: highest scored criterion.
- • Time, cost, and ease of use: compare only after and effectiveness pass.
Test evidence: For each option, record the E1-E3 result that supports or fails each criterion. Do not assign a score without a named observation.
- Version or option tested
- Criterion met or missed
- Evidence ID and result
- Revision made
- Reason for the revision
- Need and user
- Criteria and constraints
- Chosen option and evidence
- Test result
- Revision and reason
Students often think If two variables in my data move together, especially if they move together tightly, then one is causing the other.. The trap: Correlation means they move together; causation means one drives the other. They are logically different. A hidden third factor (a lurking variable) can drive both, so 'they correlate' is evidence for a relationship, not proof of a cause.
Claim: In this stream dataset, dissolved oxygen is lowest on the warmest days.\nEvidence: My graph shows dissolved oxygen held between 8.5 and 9.2 milligrams per liter on days when the water was 12 to 16 degrees Celsius, then dropped to 5.1 milligrams per liter on the day the water reached 26 degrees Celsius.\nReasoning: The warmest-day oxygen reading is about 40 percent lower than the cool-day readings, so the data supports the claim that oxygen falls as this stream warms up.\nCorrelation or causation: This is correlation. The graph shows warm water and low oxygen appearing together, but the numbers alone do not prove the warmth caused the drop.\nAlternative explanation: The warmest day was also the day after a heavy rain that washed fertilizer into the stream, and that runoff can feed bacteria that use up oxygen. Until I rule out the runoff, I can only claim that temperature and low oxygen are correlated, not that heat caused it.
This model shows the level of evidence and organization needed to complete: Models the Problem 4 CER step on a different dataset: a paragraph with a claim, cited graph data, reasoning, a correlation-vs-causation classification with justification, and one alternative explanation, so students can copy the structure without copying the answer.
- 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 the CER paragraph on Schoology today.
- 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.
Classroom documents for this lesson are posted in Schoology. Open Clever, then Schoology, and find each one by the name shown on its card.
Open this when the class reaches this activity and use it to complete the required lesson artifact.
Placement rationale
Matched Environmental data graphing and analysis by path:Biomedical-Innovations/Problem-4_Environmental-Health/4.1_Environmental-Health; keywords:environmental. Score 134. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
Use this if you were absent, got stuck, or need another pass before you submit the lesson artifact.
Placement rationale
Matched Environmental data graphing and analysis by path:Biomedical-Innovations/Problem-4_Environmental-Health/4.1_Environmental-Health; keywords:environmental. Score 130. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
Use this if you were absent, got stuck, or need another pass before you submit the lesson artifact.
Placement rationale
Matched Environmental data graphing and analysis by path:Biomedical-Innovations/Problem-4_Environmental-Health/4.1_Environmental-Health; keywords:environmental. Score 130. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
Sign in to Clever with your district Microsoft account to open Schoology or myPLTW. Follow today's posted steps. If myPLTW will not open, use the posted alternative and tell Mr. Mendoza. Turn in your completed work through the Schoology assignment.
Practice: try a question, then check your answer▸
Claim ceiling for this check: Today's evidence supports a classroom claim about CER paragraph. It cannot prove causation, diagnose a real patient, or justify action outside this room.
Your graph shows traffic volume and asthma-related nurse visits both rising across the week. A classmate writes: 'This proves cars cause asthma.' Rewrite it as a defensible CER claim.
Write an answer and pick a confidence to unlock the key.
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.
Today is individual work you can do from home: complete the same target above, then submit your CER.
Go 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.
Class still runs. Complete the online activity above (it's self-guided). Need the concept taught without a teacher? Use this authoritative explainer:
Khan Academy StatisticsYou'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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