Rough draft.This research track is under review with Dr. Atit's lab. Content and sequence may still change.
The Baby Mateo Case
Experimental Design domainBiomedical Innovations (BI)Lesson 2 of 20Your seat: Principal Investigator (PI)
From a Question to a Testable Hypothesis
Discovery question
How do we turn our PICO question into a hypothesis that an experiment could actually disprove, and what parts of the study must we control?
💡 A hypothesis is a falsifiable prediction, and every experiment must nail down what it changes, what it measures, and what it holds constant.
The plan
Prerequisite check
Before this page, you should know
- A question is researchable when it can be answered by collecting and analyzing real, observable (empirical) data; questions of blame, single fate, or value are not.
- PICO sharpens a vague question into Population, Intervention or exposure, Comparison, and Outcome.
If not, review
Today's new idea is only
A hypothesis is a falsifiable prediction, and every experiment must nail down what it changes, what it measures, and what it holds constant.
Learn first
What you will learn
Goal: Students will write a testable hypothesis and its , and identify the , , controlled variables, and for a study of Mateo's question.
Know by the end
- A hypothesis is a testable, predicted answer to a , and it must be falsifiable (some result could prove it wrong).
- The is what the researcher changes; the is what is measured; controlled variables are held the same across groups.
- A is the comparison that does not get the intervention (or gets the standard one); without it you cannot tell whether the intervention caused the outcome.
- The states no difference or no effect; scientists test the null because you can disprove no difference with data but can never fully prove a positive claim true.
Learn first
Model: Two real studies, stripped to their moving parts
Study 1 (clinical, TOPS trial) [PMID:37646677]: 558 infants with were assigned to have the palate repaired at 6 months OR at 12 months. All surgeons used the same standardized technique. At age 5, trained assessors who did not know each child's group measured (a speech problem). Result: 8.9% in the 6-month group versus 15.0% in the 12-month group.
Study 2 (laboratory, Ezh2 mouse study) [PMID:37435868]: To test whether the gene Ezh2 is needed to build the , researchers deleted Ezh2 only in the palate of some mouse embryos. Littermate embryos that still had the gene served as the comparison. They then checked each for palate. About 20% of the Ezh2-deleted embryos had a cleft palate; the littermates did not. The two studies, one clinical and one lab, share the same variable logic.
Do the work
Explore (work the model before reading on)
- In Study 1, what one thing did the researchers deliberately change between groups?
- In Study 1, what one thing did they measure at the end? In Study 2, what did they measure at the end?
- In Study 1, every surgeon used the same technique. Why would the result be hard to trust if different groups had used different techniques?
- In Study 2, the littermates that kept the gene are the comparison. What job does that comparison group do, and what could you not conclude without it?
- Suppose Study 1 had found 12.0% versus 12.0% (no difference). What would that tell us about the prediction earlier repair reduces speech problems? Could a result ever make us reject that prediction?
- In one sentence, what three kinds of variables does every well-designed experiment have to nail down before it starts?
The plan
Guided notes
1
A falsifiable hypothesis
Model start: A hypothesis is a testable, falsifiable prediction; there must be a possible result that would prove it wrong.
- A hypothesis is a testable, predicted answer to your ; it must be ____ (falsifiable), so some possible result would prove it wrong.
- Earlier repair reduces speech problems is falsifiable because finding no difference would count against it.
2
Naming the variables
- : the one thing you deliberately change (Study 1: timing of surgery; Study 2: presence or absence of the ____ gene).
- : the outcome you measure. Controlled variables: everything you hold the ____ (same) across groups so it cannot explain your result.
3
Control group and the null
- A is the comparison that did not get the intervention; without it you cannot tell whether your intervention or chance caused the outcome.
- The (H-zero) states no difference; the study checks whether the data are surprising enough to ____ (reject) it. TOPS rejected its null because 8.9% versus 15.0% made no difference hard to believe.
Explore
Reading the Research
What to read
Read the title and the abstract only, not the whole paper. Gamble C, et al. 2023. Timing of Primary Surgery for Cleft Palate (TOPS trial). N Engl J Med. [PMID:37646677]
Why this source matters
This is the published evidence behind today's idea: A hypothesis is a falsifiable prediction, and every experiment must nail down what it changes, what it measures, and what it holds constant.
Words to unlock first
Reading moves
- Skim the title and abstract first to get the gist.
- Circle the one sentence that states the main claim.
- Box the evidence the authors give for that claim.
- Mark one sentence that confuses you, and move on.
Stop point
You do not need the methods or statistics yet. If a sentence is about lab technique or math you have not learned, mark it and skip it.
Your output
Write one claim-evidence sentence: what this source claims, and the one piece of evidence that backs it up.
Where this fits
Tested on (Ohio WebXam)
Genetics of Disease · 072130
PLTW lesson
MI · Experimental Design domain · Experimental design, variables, and controls
WebXam domain
Bio-Molecular Technology
Evidence to produce
Fill in a study-design card for Mateo's surgical-timing question: hypothesis, null hypothesis, independent variable, dependent variable, two controlled variables, and control group; then write one sentence naming the result that would force you to reject your hypothesis.
Lab / skill
Biomedical Innovations (BI) · Principles of Biomedical Science (PBS)
The plan
Track your progress today
Check these off as you work through the lesson, then submit. This tells Mr. Mendoza how you're doing so he can help the class. It does not replace turning in your producible.
Use the code Mr. Mendoza gave you, not your name. Saved on this device.
Check off as you finish
- Read the Model and answered the Explore questions.
- Filled in the guided notes in my own words.
- Defined the new vocabulary with an example.
- Built the producible: Fill in a study-design card for Mateo's surgical-timing question: hypothesis, null hypothesis, independent variable, dependent variable, two controlled variables, and control group; then write one sentence naming the result that would force you to reject your hypothesis.
- Wrote my Claim, Evidence, and Reasoning exit ticket.
Pick your period and code first.
Check yourself
Exit ticket (Claim, Evidence, Reasoning)
- Claim: The TOPS trial result lets us reject its .
- Evidence: The was ____, and the study measured ____% versus ____%.
- Reasoning: A measured difference is evidence against no difference, because the data are too far apart to be comfortably explained by ____.
How this is graded (rubric)
For: Fill in a study-design card for Mateo's surgical-timing question: hypothesis, null hypothesis, independent variable, dependent variable, two controlled variables, and control group; then write one sentence naming the result that would force you to reject your hypothesis.
| Criterion | Proficient | Developing | Beginning |
|---|---|---|---|
| Complete | Every required part of the artifact is present and filled in. | Most parts are present, but one is missing or left blank. | Several parts are missing. |
| Accurate | The science and data are correct and match the evidence. | Mostly correct, with a small factual slip. | Key science or data is wrong. |
| Scientific reasoning (CER) | States a claim, backs it with specific evidence, and explains the reasoning. | Has a claim and evidence, but the reasoning is thin or missing. | Gives an answer with no evidence or reasoning. |
| Professional communication | Clear, organized, and labeled the way a clinician or scientist would write it. | Readable but disorganized or missing labels. | Hard to follow. |
| Submitted | Turned in the right way (Schoology for routine work) and confirmed. | Turned in, but in the wrong place or unconfirmed. | Not turned in. |
How the model answer scores against this rubric
- CompleteProficient: Nothing is left blank: the model fills every part of "Fill in a study-design card for Mateo's surgical-timing question: hypothesis, null hypothesis, independent variable, dependent variable, two controlled variables, and control group; then write one sentence naming the result that would force you to reject your hypothesis.".
- AccurateProficient: Every number and claim matches the case evidence.
- Scientific reasoning (CER)Proficient: It names a claim, cites the specific evidence, and explains the reasoning, not just the answer.
- Professional communicationProficient: It is organized and labeled like a real chart note.
- SubmittedProficient: It would be turned in on Schoology and confirmed.
Explore
Where this leads: careers
Principal investigator Clinical trialist Laboratory scientist
What's next: We can design a single study and predict what would prove us wrong. But two honest studies on the same question can reach opposite answers. Why do scientists trust some study designs more than others?