Separate observations from explanations
See this course’s project requirements
Prepare a desk-based investigation packet from the supplied fictional plant-height observations and a separate paper-measurement protocol.
Keep your working files in your own notebook or software. Save a private description, checklist, and work link in My Proof.
What to include
- Classify observations, hypotheses, and causal claims in a supplied scenario.
- Review a safe paper-measurement protocol and identify conditions requiring clarification or supervision.
- Create a traceable data table with units, missing-value handling, and transparent corrections.
- Construct a labeled graph or complete graph specification from the supplied dataset.
- Write a limited scientific conclusion and a final readiness note identifying required local training before real laboratory work.
Review and revise
Use these criteria to check your work and choose what to improve.
- Reasoning: observation and interpretation are clearly distinguished.
- Records: values, units, conditions, and corrections are traceable.
- Representation: graph axes and plotted values match the table.
- Boundaries: conclusions fit the design and real laboratory work is conditioned on local supervision and training.
Want more background?
The idea in everyday life
Scientific work can begin with careful description before a controlled experiment exists. It is useful to ask why something happened, but the record should make clear which parts are measured and which are proposed explanations. This lesson uses fictional observations of one plant. You will analyze the supplied record without growing, collecting, or handling any biological material.
An observation records the pattern; a hypothesis proposes an explanation.
One step at a time.
Use the sample or information you have permission to use. Keep your work as you go. You can pause between steps.
- 1
Copy the four supplied height observations with their days and units. Label the entire record fictional so it cannot be mistaken for your own collected measurements.
- 2
Write two statements directly supported by the record, such as the starting height and total change. Keep those observations separate from ideas about why growth occurred.
- 3
Classify the statement about extra light as a causal explanation requiring additional design information. List one other factor that could affect a real growth comparison.
- 4
Draft a testable question naming a compared condition, measured outcome, and time period. Treat it as a planning exercise only, with no collection or experimentation required.
- 5
Create a question page with observations, hypothesis, and missing evidence in separate boxes. Save it as the starting point for the investigation packet and later conclusion.
See how it works.
Fictional scenario: A provided record lists one plant’s height as 12 mm on day zero, 18 mm on day three, 23 mm on day six, and 27 mm on day nine. Mina writes “the recorded height increased by 15 mm across nine days,” which follows the measurements. “Extra light caused the increase” is an explanation the record cannot establish: no light comparison or controlled conditions are supplied. A testable question could ask whether otherwise comparable plants under specified light conditions differ in measured growth, but designing that question does not authorize performing an experiment.
Did you cover these?
- All four heights retain day and millimeter labels.
- Total observed change is 15 mm.
- The light claim is marked unsupported by this design.
What to finish
A scientific-question page separating fictional observations, a hypothesis, and missing evidence.
Watch for this
Treating a plausible explanation as though it was directly measured in the record.
How can I tell I understand it?
You write a measurable question and identify evidence needed beyond a single observational series.
Quick knowledge check
Answer all 3 questions. Get at least 2 right and the lesson completes automatically.
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Answer all 3 questions above and get at least 2 right. You can review the explanations and try again.
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Source & access notes · checked 2026-09-10
Opened descriptive and hypothesis-based science and inductive/deductive reasoning. Supports distinctions, with no source experiments reproduced.
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Reuse: Linked for further study. Life Starter explanations, scenarios, and assessments are original; free access alone does not grant reuse rights.
Source & access notes · checked 2026-09-10
Opened explanatory/response variables and confounding discussion. Course wording treats randomization as supporting causal inference under conditions, not as absolute proof or perfect group equality.
Access: Free public reading; no account or purchase required.
Reuse: Linked for further study. Life Starter explanations, scenarios, and assessments are original; free access alone does not grant reuse rights.
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