Graph draft
Safety gate · before any work
- Wear the required PPE, keep the bench clear, handle equipment only as directed, and know where the eyewash, sink, and spill kit are before you start.
- Human samples and data stay private: label with a code, never a name, and dispose of materials in the correct waste container, then wash your hands.
Do now
Build a clear data table and draft a graph that represents your environmental data accurately.
- Hand in
- Clean labeled data table plus a drafted graph with titled and scaled axes, outlier notes, and one trend sentence.
- Where
- Turn this in at the drop folder with your district Microsoft sign-in, or hand it to Mr. Mendoza in class. Both count as submitted. Doing the activity in myPLTW does not.
You get two school days for every day you were absent, so this deadline moves with you.
You have a column of numbers from your environmental data set. Which graph, which axes, and which outlier calls make those numbers say something true instead of something misleading?
Build a clear and draft a graph that represents your environmental data accurately.
- • Your graph has titled, scaled axes and accurate plotted data.
- • You identified and justified handling of any outlier.
- If your data is 'water samples taken every week for 10 weeks,' is time a categorical, continuous, or time-based variable, and what does that tell you about graph type?
- Name one thing a graph must have before anyone else can read it without asking you questions.
- 1Organize your data into a clean table with labeled columns and units.
- 2Choose a graph type that fits your variables.
- 3Plot the data with titled axes and an appropriate scale.
- 4Mark any outliers and decide whether to keep or flag them.
- 5Write one sentence describing the trend the graph shows.
What did this day actually feel like?
Graph draft
Straight into building the graph that carries our environmental claim. Axis honest, units labeled, standard marked as a reference line.
Week seven is doing real work here. I would have truncated that axis in February without thinking about it.
Turned in: data table → Data Tables folder
Fiction. There is no such student. The lessons, labs and dates are the real planned course; the student, the classmates and the conversations are invented.
The same day, drawn.
Straight into building the graph that carries our environmental claim. Axis honest, units labeled, standard marked as a reference line.
Fiction. There is no such student. The lessons, labs and dates are the real planned course; the student, the classmates and the conversations are invented.
🛠 Get unstuck · pick your level
Lab day: Tier 1 is the whole class at the bench. No extension today.
🔑 Today's words · 5
Tap a word in the lesson for a plain meaning and one example. Recycled into next week's Do-Now.
Do the work · 80-minute blockfirst 5 min = hook▸
💡 Big idea: 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.
- 0-5 minWarm-up: which graph type would best show how air quality changes over a week?
- 5-20 minClean and label your with column headers and units
- 20-40 minChoose graph type and plot data with titled, scaled axes
- 40-55 minIdentify outliers; note your decision to keep or flag each one
- 55-70 minWrite one trend sentence based on the graph
- 70-80 minExit ticket: submit graph draft and trend sentence
- • Welcome back after the break. Today we turn raw environmental numbers into a readable graph.
- • A graph is only as good as the behind it, so we start there.
- • Graph type selection is a real decision: bar, line, or scatter each tell a different story.
- • By the end of class you'll have a draft graph and one trend sentence ready for Thursday.
- • Graph type selection depends on whether your variables are categorical, continuous, or time-based.
- • Axis titles and units are required; a graph without them cannot be interpreted by anyone else.
- • An outlier decision must be justified, not silently dropped.
Data tables, graphical claims, variables, outliers, correlation vs causation. · Graph draft
Day 1 of this lesson. Open this exact section in myPLTW (find it in Clever, Microsoft sign-in), then do the work below.
Do this: Open Problem 4 in your myPLTW course shell and navigate to the current graphing activity, then build a clean and draft a graph that represents your environmental data.
Attach your graph draft to the Problem 4 evidence portfolio.
The two no-school days are behind you; graph drafts are a mid-unit milestone, so confirm you are on pace and submit by end of today.
Draft graph with trend sentence uploaded as today's evidence.
The official PLTW activity stays inside myPLTW. If myPLTW will not open, use F1 and E1-E3 on this page to complete today's local evidence decision, then make up the official activity when access returns. Turn this in at the drop folder with your district Microsoft sign-in, or hand it to Mr. Mendoza in class. Both count as submitted. Doing the activity in myPLTW does not.
Check things off as you work, then submit. This tells Mr. Mendoza how you're doing so he can help the class. It does not replace turning in your producible through the submission route shown below.
Use the code Mr. Mendoza gave you, not your name. Saved on this device.
Data tables, graphical claims, variables, outliers, correlation vs causation. · Graph draft
Open Problem 4 in your myPLTW course shell and navigate to the current graphing activity, then build a clean and draft a graph that represents your environmental data.
The two no-school days are behind you; graph drafts are a mid-unit milestone, so confirm you are on pace and submit by end of today.
This is how Mr. Mendoza sees the class keeping pace with PLTW. Be honest, it only helps if it is accurate.
🎯 Build a clear and draft a graph that represents your environmental data accurately.
- Organize your data into a clean table with labeled columns and units.
- Choose a graph type that fits your variables.
- Plot the data with titled axes and an appropriate scale.
- Mark any outliers and decide whether to keep or flag them.
- Write one sentence describing the trend the graph shows.
Data table: Clean labeled plus a drafted graph with titled and scaled axes, outlier notes, and one trend sentence.
Turn this in at the drop folder with your district Microsoft sign-in, or hand it to Mr. Mendoza in class. Both count as submitted. Doing the activity in myPLTW does not. Use the checklist just below and upload by 11:29 PM for full credit. Absent with an excused absence? You get two school days for every day you were absent, so this deadline moves with you.
| Task | Who |
|---|---|
| Organize your data into a clean table with labeled columns and units. | _______ |
| Choose a graph type that fits your variables. | _______ |
| Plot the data with titled axes and an appropriate scale. | _______ |
| Mark any outliers and decide whether to keep or flag them. | _______ |
| Write one sentence describing the trend the graph shows. | _______ |
Working solo? Put your own name in "Who" for every row.
- Your graph has titled, scaled axes and accurate plotted data.
- You identified and justified handling of any outlier.
- 1Do thisBuild a clear data table and draft a graph that represents your environmental data accurately.
- 2Use this resource
- 3Submit thisData table: Clean labeled data table plus a drafted graph with titled and scaled axes, outlier notes, and one trend sentence.
- 4Submit it here
- 1Open the drop folder.
- 2Sign in with your district Microsoft account, not a personal one.
- 3Upload the file, named Lastname_Firstname__Assignment Title.
- 4Your own upload panel says Uploaded with a green check: that is your receipt.
Turn this in at the drop folder with your district Microsoft sign-in, or hand it to Mr. Mendoza in class. Both count as submitted. Doing the activity in myPLTW does not. Biotechnology for Health (Biomedical Innovations) › Data tables, graphical claims, variables, outliers, correlation vs causation. › Data tableOpen the drop folder
Learn it · deck, reading, 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.
Evidence can only drive a decision when it is integrated, cited, and readable by the people at risk, so a complete exposure map joins pathway, dose, and mitigation into one document a non-scientist can act on and confirms it in the tracker to close the Problem 4 loop.
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 detective board holds observations, possible explanations, and one next question.
- Which notes are direct observations?
- Which notes are explanations?
- What new evidence would separate the explanations?
Keep observations separate from explanations, then collect the evidence that can distinguish the options.
Biomedical investigations use controlled procedures and validated measurements, not intuition alone.
- • Board notes map to E1-E3.
- • Possible explanations map to the decision options.
- • The next question maps to the evidence-based action.
Driving question: You have a column of numbers from your environmental data set. Which graph, which axes, and which outlier calls make those numbers say something true instead of something misleading?
What you already know: Evidence can only drive a decision when it is integrated, cited, and readable by the people at risk, so a complete exposure map joins pathway, dose, and mitigation into one document a non-scientist can act on and confirms it in the tracker to close the Problem 4 loop.
New idea: 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.
Visual or model: F1. F1. A lesson illustration or teaching diagram for Graph draft. 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 Graph draft.
- Organize the observation with a stable evidence ID.
- Apply this rule: Keep observations separate from explanations, then collect the evidence that can distinguish the options.
- Choose the option the evidence supports and state the limit of the conclusion.
Real biomedical example: You have a column of numbers from your environmental data set. Which graph, which axes, and which outlier calls make those numbers say something true instead of something misleading?
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.
- • graph: A visual display of data, such as a bar, line, or scatter plot, that makes patterns and relationships easier to see than a table of numbers.
- • trend: The general direction that data moves over time, such as rising, falling, or staying steady, seen across many points rather than a single value.
- • outlier: A data point that lies far away from the rest of the values in a set, which may signal an error or a genuinely unusual result.
- • error: The difference between a measured value and the true value, caused by limits of instruments, method, or the person measuring.
- • correlation: Two things tending to occur together, which does not by itself prove that one causes the other.
- • causation: When one factor actually brings about another, shown by controlled evidence rather than by the two simply appearing together.
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.
Graph type selection depends on whether your variables are categorical, continuous, or time-based.
Limit: E1 supplies context or an observation; it does not by itself establish the explanation.
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.
Limit: E2 is a teaching statement or comparison and must be checked against the task evidence.
Your graph has titled, scaled axes and accurate plotted data.
Limit: E3 supports only the result or product criterion named here; it cannot justify a broader clinical or causal claim.
PLTW-BFH-2027-04-13 · Simulated classroom evidence scenario
Your role: biomedical design team member
Decision: Your team must decide what the evidence from Graph draft supports before submitting the labeled and result claim named on the lesson page.
- • Select the option best supported by E1-E3.
- • Select a reasonable alternative and name the evidence it would require.
- • Delay the claim because the evidence does not distinguish the options.
Response: State one choice, cite at least two evidence IDs, explain the rule that connects them, and add one limitation. Submit it as the labeled and result claim.
Claim ceiling: The supplied lesson evidence can support an observation, pattern, classroom mechanism, or next-step decision about Graph draft. It cannot by itself prove causation, establish a real clinical diagnosis, or justify action outside this classroom task.
Mean = sum of values / number of values. Median = middle ordered value. Range = maximum - minimum.
For 2, 4, 4, and 10: mean = 20 / 4 = 5, median = 4, and range = 10 - 2 = 8.
Mean, median, and range keep the measurement unit. Order the values before finding the median.
Calculate the requested summary for today's supplied values, then write what it reveals and what it hides.
Students often think Any data can go on any graph, and a bar chart versus a line graph is just a style choice you make to look nice.. The trap: Graph type is a claim about your variables, not a style pick. Bar charts compare separate categories; line graphs show change across a continuous or time axis. Using the wrong one tells the reader a relationship exists (or does not) that your data never showed.
Data: monthly average air particulate (PM2.5) near a roadway, units micrograms per cubic meter.
Clean table columns: Month, PM2.5 (micrograms/m3).
Values: Jan 14, Feb 13, Mar 12, Apr 11, May 9, Jun 35.
Graph choice: line graph, because the variable (month) is time-ordered and I want to show change over time.
Axes: x-axis = Month; y-axis = PM2.5 (micrograms/m3), scaled 0 to 40. Title: 'Monthly Roadway PM2.5'.
Outlier: June (35) is far above the others. I flagged it rather than deleting it, and noted a possible cause (a nearby wildfire smoke event), so the reader can decide how to treat it.
Trend sentence: Particulate levels declined from January through May, then spiked sharply in June.
| Month | PM2.5 (ug/m3) |
|---|---|
| Jan | 14 |
| Feb | 13 |
| Mar | 12 |
| Apr | 11 |
| May | 9 |
| Jun | 35 (outlier, flagged) |
This model shows the level of evidence and organization needed to complete: Completes the Problem 4 graph-draft step: an organized data table plus a drafted graph with titled, scaled axes, an outlier decision, and a one-sentence trend statement.
- 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: Submit your data table and graph draft on the class site 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.
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 Graph draft. 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.
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).
How to get there: open Clever and sign in with your Microsoft (district) account. Both myPLTW and Schoology are in Clever. Do the activity in myPLTW. Turn the work in on this site or hand it to Mr. Mendoza, because that is the step that counts as submitted. Schoology only shows your report-card grade later.
Check yourself · commit, then reveal▸
Claim ceiling for this check: The supplied lesson evidence can support an observation, pattern, classroom mechanism, or next-step decision about Graph draft. It cannot by itself prove causation, establish a real clinical diagnosis, or justify action outside this classroom task.
Your data is monthly air-quality readings for one year. A classmate plots them as a bar chart with the y-axis starting at 40. Name the two problems and fix them.
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.
Go further and get help▸
I can name the procedure's purpose and the evidence I will record. I can identify each named hazard and the control that reduces it: Wear the required PPE, keep the bench clear, handle equipment only as directed, and know where the eyewash, sink, and spill kit are before you start. My data table is ready before materials are handled.
Finish the checklist before you handle any material.
- • Wear the required PPE, keep the bench clear, handle equipment only as directed, and know where the eyewash, sink, and spill kit are before you start.
- • Human samples and data stay private: label with a code, never a name, and dispose of materials in the correct waste container, then wash your hands.
- 1Before materials are handled, identify the purpose, variables or comparison, controls, measurement units, and stop-work condition.
- 2Organize your data into a clean table with labeled columns and units.
- 3Choose a graph type that fits your variables.
- 4Plot the data with titled axes and an appropriate scale.
- 5Mark any outliers and decide whether to keep or flag them.
- 6Write one sentence describing the trend the graph shows.
- 7Record each result in the prepared table before interpreting it. Mark missing, repeated, or invalid results truthfully.
- 8Complete the named cleanup and waste route, remove PPE safely, wash hands when required, and confirm the station is ready for the next group.
| Trial or sample ID | Independent condition | Measured result with units | Observation before interpretation | Quality-control note |
|---|---|---|---|---|
Before the procedure, predict the result and cite the rule behind the prediction.
After the procedure, compare the result with the prediction and name one limitation or source of uncertainty.
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 Data table.
Open the drop folderTurn this in at the drop folder with your district Microsoft sign-in, or hand it to Mr. Mendoza in class. Both count as submitted. Doing the activity in myPLTW does not.
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.
- SubmittedTurned in the right way, on the class site or handed to Mr. Mendoza in class, and confirmed. Not in Schoology: that is where the report-card grade appears later.
- Error analysis and method · counts doubleName a specific limit of the method and how it moved your result, and compare what you predicted to what happened. "Human error" does not count; say what about the procedure or instrument caused it.