Experimental vs observational studies, sample size, graphing, mean, SD, t-test purpose.
What to do if absent- 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.
Week overview - Reading the body's data: study types, sample size, and the t-test
Collect physiological data with sensors, organize it in a spreadsheet, compute mean and standard deviation, and explain when a t-test is appropriate.
- 1Decide whether your sensor activity is an experimental or observational study and write why.
- 2Collect at least ten readings with the sensor so your sample size is large enough to graph.
- 3Enter your readings into the spreadsheet, one value per row, with clear column headers.
- 4Use the spreadsheet to calculate the mean and standard deviation of your readings.
- 5Make a graph that shows the spread of your data, not just a single average.
- 6Write one sentence explaining why a t-test would compare two groups of your data.
- • You will be able to tell an experimental study from an observational one.
- • You will be able to compute mean and standard deviation from data.
- • You will be able to explain the purpose of a t-test.
Daily lessons this week
Open any day for its full lesson, the work due that day, and guided notes.
CER contribution arguing an ethical limit for physiological data collection and storage, plus two questions and a reflection connecting the argument to the Wednesday lab plan.
Study design decision: experimental vs. observational classification with justification, plus a sample-size estimate and rationale for the Wednesday lab.
Raw physiology data table: labeled trials, baseline and treatment conditions, measurement values with units, and a brief condition-control note.
Statistics practice: mean and standard deviation calculated for each condition with steps shown, plus a written explanation of what a t-test compares and whether it applies to the data.
Complete physiology data table: all trials labeled with conditions and units, summary statistics (mean and SD) per condition, and a one-line reliability assessment.
Quick intro to the week
- Hook: your own pulse is a dataset, and learning to read it is how physiology becomes evidence.
- Today's goal: collect real sensor data and summarize it honestly with mean, spread, and a graph.
- Monday's bioethics debate on data ethics applies directly: whose body data is this, and who may use it?
- Reminder: your graded spreadsheet and analysis live in the PLTW course shell.
Your PLTW coursework this week
Do this: Advance PLTW Problem 2 by collecting and summarizing physiological sensor data in the online course shell.
- • Experimental studies manipulate a variable; observational studies only watch.
- • Standard deviation measures how spread out data are around the mean.
- • Compute mean and standard deviation in a spreadsheet.
- • Explain when a t-test is used to compare groups.
📋 PLTW evidence due: physiology sensor spreadsheet with mean, standard deviation, and a graph in the course shell.
All PLTW activities are completed inside the PLTW course environment — this page only gives direction.
This week's PLTW tracker
Your week at a glance. Check off each deliverable as you finish it, then submit so Mr. Mendoza can see how the class is pacing.
Use the code Mr. Mendoza gave you, not your name. Saved on this device.
| Day | Date | Focus | Key deliverable |
|---|---|---|---|
| Monday | Wed, Feb 24 | Data-ethics debate | CER contribution arguing an ethical limit for physiological data collection and storage, plus two questions and a reflection connecting the argument to the Wednesday lab plan. |
| Tuesday | Thu, Feb 25 | Experimental vs observational | Study design decision: experimental vs. observational classification with justification, plus a sample-size estimate and rationale for the Wednesday lab. |
| Wednesday | Fri, Feb 26 | Physiology sensor lab | Raw physiology data table: labeled trials, baseline and treatment conditions, measurement values with units, and a brief condition-control note. |
| Thursday | Mon, Mar 1 | Mean, SD, t-test | Statistics practice: mean and standard deviation calculated for each condition with steps shown, plus a written explanation of what a t-test compares and whether it applies to the data. |
| Friday | Tue, Mar 2 | Submit data table | Complete physiology data table: all trials labeled with conditions and units, summary statistics (mean and SD) per condition, and a one-line reliability assessment. |
- M: data ethics debate
- T: variable practice
- W: data collection
- Th: stats practice
- F: data table submit
Due by week's end: Physiology data table.
Lab day — what to bring & watch
This explainer accompanies the PLTW lab protocol — watch it before lab.
What to do when absent
Most days, this class is your PLTW coursework — and PLTW is online and individual. So being out usually just means doing exactly what we did in class, from home.
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.
You can't do those from home — do this instead: Spreadsheet dataset.
Class still runs. A substitute will post today's plan — complete the online activity above; it's built to be self-guided. Need the concept taught without a teacher? Use this authoritative explainer:
Khan Academy Statistics and ProbabilityVocabulary
Virtual resources
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 Human physiology data and research design by path:Biomedical-Innovations/Problem-2_Human-Physiology/2.1_Human-Physiology; keywords:physiology, research design. Score 142. 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 Human physiology data and research design by path:Biomedical-Innovations/Problem-2_Human-Physiology/2.1_Human-Physiology; keywords:physiology, research design. Score 142. 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 Human physiology data and research design by path:Biomedical-Innovations/Problem-2_Human-Physiology/00_Problem-Overview; keywords:physiology, research design. Score 138. 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.
Standards this week
WebXam practice
Drop your Week 6 here. Use a clear file name (your initials + project). Routine work still goes to Schoology (via the CMSD portal).
Upload a project