Separate a result from its explanation
Can group composition explain a reported tool advantage?
Entering midway? Revisit Create an honest chart specification for the preceding worked example, or start here and use the explanation below.
Start with a concrete question
Authored cohort comparison: experienced participants finish all tasks and new participants finish half. Tools have no causal effect in this fixture.
Try the initial inputs, then write a prediction before changing one setting. All calculations run locally on your CPU.
What do you expect?
Before changing a setting: Can group composition explain a reported tool advantage? Write what you expect and why.
Change one thing. Inspect what happens.
- Compute completion in each unbalanced group.
- Choose a claim and inspect what it assumes.
- Balance the groups while holding within-group outcomes fixed.
- Write a results paragraph separating observation, explanation and next test.
Your settingsMechanism
Calculation belowEvidence
Compare outcomes
Compare the current results
Every bar starts at zero and uses the same numeric scale in this chart. The upper bound automatically adjusts to the largest current value (at least 1), so compare the numbers when changing inputs. Units and quantities come from each label; different kinds of quantity are not interchangeable. Displayed values are rounded to at most six significant digits.Follow the calculation
- Unbalanced fixture: A has 80 experienced and 20 new participants; B has 20 experienced and 80 new participants.
- Experienced participants finish 100% of tasks, new participants 50%; the tool has no effect in this fixture.
- A: 90%; B: 60%.
- Claim: “A and B have different observed completion rates in this cohort.”
- The wording must be checked against the selected allocation and observed rates.
Distinguish a descriptive result, an explanation hypothesis and a causal conclusion. Changing the group mix can remove a difference without changing any tool.
Revise a research results paragraph
Write a descriptive finding, an alternative explanation and a proposed test. Use the selected fixture allocation and state what it cannot establish.
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Compare with my earlier draft
Tool A caused completion to rise from 60% to 90%. We should replace every other tool.
Explain what you changed and why in your observation notes. Text differences do not establish quality.
Inspect an example solution after your attempt
In the unbalanced fixture, group A completed 90% and B 60%. A had more experienced participants. The supplied within-experience outcomes are identical, so the difference does not show a tool effect. Balance allocation and measure a predefined outcome before making a causal claim.
This is one worked example. Test another input and explain its limitations.
Captures keep your inputs, prediction and observation. Results are recalculated from those inputs. Resetting inputs keeps your captures and challenge history.
Explain the mechanism
Separate a result from its explanation
Authored cohort comparison: experienced participants finish all tasks and new participants finish half. Tools have no causal effect in this fixture.
Follow the mechanism
The unbalanced groups differ because their experience mixes differ.
Balanced groups both finish 75%: half experienced at 100%, half new at 50%.
A causal claim needs a design and evidence that address alternative explanations.
Worked example
Unbalanced fixture: A has 80 experienced and 20 new participants; B has 20 experienced and 80 new participants.
Experienced participants finish 100% of tasks, new participants 50%; the tool has no effect in this fixture.
A: 90%; B: 60%.
Claim: “A and B have different observed completion rates in this cohort.”
The wording must be checked against the selected allocation and observed rates.
Calculation
Completion = experienced share × 100% + new share × 50%.
Try a controlled comparison
Compute completion in each unbalanced group.
Choose a claim and inspect what it assumes.
Balance the groups while holding within-group outcomes fixed.
Write a results paragraph separating observation, explanation and next test.
What this does not establish
- All messages, people, documents and outcomes here are original fictional teaching fixtures; results are not measurements of real organizations.
Try a fresh case
A group contains 40 experienced users with 100% completion and 60 new users with 50% completion. What percentage of all 100 users complete?
This is a public practice check. Retries support learning; matching a number does not certify independent proficiency.
Take the investigation further
Choose any extension. These are project prompts for you to carry out; they are not automatically assessed.
School investigation
Create a new case with different numbers and explain your decision to a classmate.
College investigation
Implement or analyze a fresh case, document assumptions and compare at least two alternatives.
Workplace investigation
Prepare a decision artifact with evidence, operating constraints, an owner and a follow-up measurement.
Keep the evidence, choose your next step
Completion records your own decision that you have worked through this investigation. Practice checks and independent project evidence are separate.