Lab Analysis
Overview
Analyze how models are used in laboratory experiments and how experimental data can improve models.
Practice Problems
Question 1: Students used a model to predict that a ball dropped from 2 meters would hit the ground in 0.64 seconds. The actual time was 0.72 seconds. What might explain the difference?
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Answer: The model likely ignored air resistance; real-world factors the model simplified caused the difference
Models always simplify reality. Identifying what was simplified helps explain prediction errors.
Question 2: A population growth model predicts exponential growth, but lab data shows the population leveling off. How should the model be revised?
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Answer: Add carrying capacity - the model needs to account for limited resources
The logistic growth model (with carrying capacity) better represents real populations than pure exponential.
Question 3: In a stream table model of erosion, water flows much faster relative to size than in real rivers. How does this affect conclusions?
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Answer: Erosion patterns may form faster/more dramatically than in nature; time scales don't translate directly
Physical models often compress time or exaggerate effects. Acknowledge this when drawing conclusions.
Question 4: A cell model made of craft materials shows organelles as different colored shapes. What can't this model show?
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Answer: Movement, chemical processes, interactions between organelles, 3D structure, actual scale
Static physical models can't represent dynamic processes or molecular-level activity.
Question 5: Lab data shows: Trial 1: 4.2 s, Trial 2: 4.1 s, Trial 3: 4.3 s, Trial 4: 8.7 s. The model predicts 4.2 s. How should this data be interpreted?
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Answer: Trial 4 is an outlier (likely error); Trials 1-3 support the model; investigate what went wrong in Trial 4
Don't automatically discard outliers - determine if they're errors or meaningful data.
Question 6: A student's molecular model shows atoms as solid spheres touching each other. What limitation does this create?
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Answer: Atoms aren't solid spheres - they're mostly empty space with electron clouds; bond lengths aren't to scale
This model is useful for showing molecular structure but misleading about atomic nature.
Question 7: Weather models become less accurate further into the future. Why?
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Answer: Small uncertainties compound over time; weather is a chaotic system where tiny changes have large effects
This is why 10-day forecasts are less reliable than 2-day forecasts - "butterfly effect."
Question 8: A circuit model uses water flowing through pipes to represent electricity. What matches well and what doesn't?
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Answer: Matches: flow/current, pressure/voltage, pipe width/resistance. Doesn't match: electrons aren't water molecules, electricity moves at near light speed
Analogies help understanding but always break down at some point.
Question 9: Two student groups built models of the same enzyme. Group A used clay; Group B used computer simulation. Compare their usefulness.
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Answer: Clay: Good for visualizing 3D shape, hands-on learning. Computer: Can show movement, binding, molecular interactions, more accurate shape
Different model types serve different purposes; neither is "better" in all ways.
Question 10: How does the process of modeling connect to the scientific method?
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Answer: Models generate predictions (hypotheses) that can be tested; data either supports the model or suggests revisions
Modeling is cyclical: Create model, make predictions, test, revise model based on results.