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6.3.2Inquiry Process

Evaluating in Biology — IB Biology HL Revision Notes & Topical Questions

5 min read 6 parts Lesson 160 of 160

📚 IB Biology HL Hub / Topical Revision
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Curriculum Equation Key قوانين الرقم الهيدروجيني والاتزان الأيوني - pH & Acid-Base Equilibrium FormulasFast Exam Solution
pH = -log[H⁺] | pOH = -log[OH⁻] | pH + pOH = 14 | [H⁺][OH⁻] = 10⁻¹⁴
Word Equation & Conditions: الرقم الهيدروجيني = -لوغاريتم تركيز أيون الهيدروجين | pH + pOH = 14
Location & Specifications: الاتزان الأيوني، كيمياء 3 ثانوي، التحصيلي، و AP Chemistry.
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Section 1 of 6Evaluating the Hypothesis

The evaluation follows on from the conclusion and asks how far the evidence can be trusted.

Evaluating the Hypothesis
Strength of support
  • Strength of support Even if the data support the hypothesis, comment on how firmly, taking the uncertainties and errors you found into account.
Spread of data
  • Spread of data A large standard deviation at one condition, such as 50 °C in an enzyme study, weakens claims made about that exact point.
Effect on result
  • Effect on result Say how an error could change the key outcome, for example by shifting an optimum value or hiding a difference between means.

Section 2 of 6Types of Error

Distinguishing the two types of error is the most important part of an evaluation.

Systematic error
  • Systematic error A fault in method or apparatus that pushes every result the same way, such as a pH meter that always reads 0.5 units too high.
Random error
  • Random error Unpredictable variation between measurements, often caused by natural differences between biological samples such as potatoes.
Systematic example
  • Systematic example Water evaporating from potato cylinders before final weighing makes every final mass too low and exaggerates water loss.
Random example
  • Random example Judging a colour change endpoint by eye gives results that vary with reaction time and perception.
Reducing them
  • Reducing them Repeats and averaging reduce random error, while calibration or a changed procedure is needed to remove systematic error.
PropertySystematic errorRandom error
DirectionAlways the same wayVaries either way
AffectsAccuracyPrecision
Removed byBetter method or calibrationMore repeats and averaging

Section 3 of 6Weaknesses, Limitations and Assumptions

Weakness
  • Weakness A feature of the method causing significant error, such as measuring a non-circular inhibition zone with a ruler where parallax is large.
Limitation
  • Limitation A factor restricting how far the conclusion applies, such as testing only one potato species so results cannot be generalised to others.
Assumption
  • Assumption A simplification made in the design, such as assuming mass changed only because of water movement when ions may also have leaked out.
Control gaps
  • Control gaps Variables that were not fully controlled, like temperature drifting in a water bath, reduce the validity of the comparison.

Section 4 of 6Proposing Improvements

1
Take each significant weakness or error identified and pair it with one specific improvement that targets that exact problem.
2
Make sure the change is realistic for a school laboratory, for example using a colorimeter or digital image analysis instead of judging by eye.
3
Explain how the improvement would reduce the error, such as removing human judgement of an endpoint so timings become consistent.
4
Where useful, suggest extending the work with more species or a narrower range of the independent variable to widen the conclusion.

Section 5 of 6Worked Example

Question

  • A 10.0 cm³ volume is measured with a measuring cylinder of uncertainty ±0.5 cm³.
  • Calculate the percentage uncertainty and compare it with a burette of uncertainty ±0.05 cm³.

  1. Percentage uncertainty (cylinder) = (0.5 ÷ 10.0) × 100 = 5%.
  2. Percentage uncertainty (burette) = (0.05 ÷ 10.0) × 100 = 0.5%.
  3. Ratio = 5 ÷ 0.5 = 10, so the burette is ten times less uncertain for this volume.

Answer The cylinder gives 5% uncertainty and the burette 0.5%, so switching to a burette is a relevant and realistic improvement.

Section 6 of 6Exam Checklist & Tips

6.3.2 – Key Points for the Exam

  • Systematic error An error that shifts all measurements in the same direction and reduces accuracy.
  • Random error Unpredictable variation in measurements that reduces precision.
  • Limitation A factor that restricts the scope over which a conclusion can be applied.
  • Assumption A simplification accepted in the design of an experiment without being tested.
  • Percentage uncertainty The absolute uncertainty divided by the measured value, times 100.

Common Mistakes

  • Listing vague errors such as human error instead of naming a specific source and how it affected the data.
  • Suggesting improvements that are unrealistic in a school laboratory or that do not address the stated weakness.
  • Mixing up limitations, which restrict the conclusion, with weaknesses, which cause error in the data.
  • Saying more repeats will fix a systematic error, when repeats only reduce random error.

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