Bias, error, graph choice
Identify sources of bias and error and choose the right graph for your physiology data.
Draft graph showing the physiology comparison with labeled axes, units, a title, and an annotated bias-and-error note.
- 1Do thisIdentify sources of bias and error and choose the right graph for your physiology data.
- 2Use this resource
- 3Submit thisData table: Draft graph showing the physiology comparison with labeled axes, units, a title, and an annotated bias-and-error note.
- 4Submit it here
- 1CMSD website. Go to clevelandmetroschools.org and click the Clever button.
- 2Clever. Clever opens. Sign in if it asks.
- 3Microsoft (district) login. Use your district Microsoft account (the one for school).
- 4Schoology. Open Schoology, then your class, then Assignments, and find the file named below.
The file to submit is named: Biotechnology for Health (Biomedical Innovations) › Bias, error, graph choice, CER conclusion, limitations. › Data tableOpen 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 — you open it through Schoology.
Minute-by-minute · 80-minute block
💡 Big idea: Choosing the right graph for your data is not an aesthetic decision -- the wrong graph can obscure or distort the pattern your study was designed to detect.
- 0-10Introduce bias versus measurement error: definitions and examples in physiology studies
- 10-30List possible bias and error sources specific to your own study
- 30-50Choose a graph type: bar, line, scatter, or box plot -- justify the choice for your comparison
- 50-65Draft the graph with labeled axes, units, and a title
- 65-77Add a bias-and-error annotation note on the graph and submit
- 77-80Exit check: which bias source is most likely to affect your conclusion and why?
- • Before you run your statistics, you need to know what could have gone wrong with your data.
- • Today you will name the bias and measurement-error sources in your study and choose the graph that best shows your comparison.
- • A graph that hides important variation is a misleading graph -- you will learn to make graphs that reveal what the data actually says.
- • Graph literacy and error analysis appear in the data-analysis skills tested by WebXam 072125.
- 1List possible sources of bias and measurement error in your study.
- 2Decide which graph type best shows your comparison.
- 3Draft the graph with labeled axes and units.
- 4Note how bias or error could affect what the graph shows.
- 5Submit your graph draft with a bias-and-error note.
- • You can name specific bias and error sources in your study.
- • You can justify your graph choice for the comparison.
- • The specific bias and measurement-error sources that threaten validity in a physiology study.
- • How to select the appropriate graph type for a comparison between two conditions.
- • How acknowledged bias or error must appear in any honest data interpretation.
Your PLTW work today
Bias, error, graph choice, CER conclusion, limitations. · Bias, error, graph choice
Day 2 of this lesson. Open this exact section in myPLTW (reached through Schoology), then do the work below.
Do this: Open Problem 2 in your myPLTW course shell and locate the graphing or data-visualization activity to review the graph format requirements.
Mark the graphing activity complete in your tracker after submitting your graph draft.
The biometric-privacy CER is done; by end of today your draft graph with labeled axes and a bias-and-error note should be submitted.
Draft graph with labeled axes, units, and a bias-and-error annotation note submitted to Schoology.
All PLTW activities are completed inside the PLTW course environment — this page only gives direction. Submit producibles on Schoology.
Today's PLTW tracker
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 on Schoology.
Use the code Mr. Mendoza gave you, not your name. Saved on this device.
Bias, error, graph choice, CER conclusion, limitations. · Bias, error, graph choice
Open Problem 2 in your myPLTW course shell and locate the graphing or data-visualization activity to review the graph format requirements.
The biometric-privacy CER is done; by end of today your draft graph with labeled axes and a bias-and-error note should be submitted.
This is how Mr. Mendoza sees the class keeping pace with PLTW. Be honest, it only helps if it is accurate.
🎯 Identify sources of bias and error and choose the right graph for your physiology data.
- List possible sources of bias and measurement error in your study.
- Decide which graph type best shows your comparison.
- Draft the graph with labeled axes and units.
- Note how bias or error could affect what the graph shows.
- Submit your graph draft with a bias-and-error note.
Data table: Draft graph showing the physiology comparison with labeled axes, units, a title, and an annotated bias-and-error note.
Submit on SchoologyUpload by 11:29 PM for full credit.
| Task | Who |
|---|---|
| List possible sources of bias and measurement error in your study. | _______ |
| Decide which graph type best shows your comparison. | _______ |
| Draft the graph with labeled axes and units. | _______ |
| Note how bias or error could affect what the graph shows. | _______ |
| Submit your graph draft with a bias-and-error note. | _______ |
Working solo? Put your own name in "Who" for every row.
- You can name specific bias and error sources in your study.
- You can justify your graph choice for the comparison.
Teacher-posted resources
Classroom documents for this lesson. Ones marked “Open the file” open right here; the rest are posted in Schoology. Use the label on each card to choose the right move.
Use this if you were absent, got stuck, or need another pass before you submit the lesson artifact.
Placement rationale
Matched Statistical analysis and t-test reasoning by path:Biomedical-Innovations/Problem-2_Human-Physiology/2.1_Human-Physiology; keywords:statistical analysis. Score 138. 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 Statistical analysis and t-test reasoning by path:Biomedical-Innovations/Problem-2_Human-Physiology/2.1_Human-Physiology; keywords:statistical analysis. Score 134. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
Open this when the class reaches this activity and use it to complete the required lesson artifact.
Placement rationale
Matched Statistical analysis and t-test reasoning by path:Biomedical-Innovations/Problem-2_Human-Physiology/2.1_Human-Physiology. Score 126. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
How to get there: open the CMSD website, click Clever, sign in with your Microsoft (district) account, then open Schoology from Clever.
Lab & supplies
WebXam practice
Cumulative WebXam review
A quick mixed-review pulling questions from earlier units plus today, so the WebXam material stays fresh.
Where this leads — careers
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.
What to do if you were absent
Today is individual PLTW work, so do exactly what we did in class, from home: complete the same PLTW target above, then submit your Data table.
Open Schoology (CMSD) and keep goingHow to get there: open the CMSD website, click Clever, sign in with your Microsoft (district) account, then open Schoology from Clever.
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 Statistics and Probability- 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 (Schoology for routine work) and confirmed.
Drop your Thu, Mar 4, 2027 · Bias, error, graph choice here. Use a clear file name (your initials + project). Routine work still goes to Schoology (via the CMSD portal).
Upload a project