Inquiry 3: Concluding and evaluating — IB Chemistry SL Revision Notes & Topical Questions

Section 1 of 16Purpose of a conclusion

Definition

• Definition a brief, focused summary of the findings.

Aim

• Aim a clear, concise answer to the research question, based only on evidence from the data analysis.

Broader link

• Broader link a strong conclusion relates the findings to scientific principles and accepted values.

Nothing new

• Nothing new no new ideas or explanations are introduced; it only summarises what was analysed.

Section 2 of 16Justifying the conclusion with data

Direct answer

• Direct answer start with a direct answer to the research question using the trend found in the interpretation.

Supporting evidence

• Supporting evidence quote key processed data such as a final concentration, a graph gradient or an experimental enthalpy change.

Fit

• Fit comment on how well the line fits the points, for example using R².

Final result

• Final result always give the final result with its uncertainty.

Section 3 of 16Relating the result to the hypothesis

Support or refute

• Support or refute state explicitly whether the results support or refute the hypothesis.

Unsupported hypothesis

• Unsupported hypothesis this is a valid scientific finding and not a failed experiment.

Reasons

• Reasons reasons for a discrepancy are suggested in the evaluation.

Theory link

• Theory link connect the finding to the chemical theory, for example collision theory predicts that higher concentration gives more frequent effective collisions.

Limit of claim

• Limit of claim claim only what the data show; if the data are inconclusive, say so.

Section 4 of 16Comparing with accepted values

Literature value

• Literature value compare with values from the IB data booklet, textbooks or other reliable sources.

Cite the source

• Cite the source state the literature value and where it came from.

Quantify

• Quantify calculate the percentage error rather than saying the result was "close".

Accuracy

• Accuracy the comparison allows a comment on the accuracy of the outcome.

• Percentage error = (accepted value − experimental value) / accepted value × 100.

Section 5 of 16Impact of uncertainty on the conclusion

1Confidence

• Confidence the propagated uncertainty determines the confidence in the final result.

2Percentage error larger than percentage uncertainty

• Percentage error larger than percentage uncertainty the deviation is not just due to limits of the instruments.
• The main cause is likely a systematic error in the methodology.

3Literature value inside the uncertainty range

• Literature value inside the uncertainty range the result is consistent with the accepted value despite errors.

4Wording

• Wording say "consistent with" when only a limited range of values was tested, rather than "proves".

Section 6 of 16Structure of a strong conclusion

1

State what the data show, with a value and uncertainty.

2

Justify it with the trend, gradient or calculated value that supports it.

3

Link it to chemical theory.

4

Compare with the literature value using percentage error and uncertainty.

5

Keep it short and direct.

Section 7 of 16More from the specification

More from the specification

Evaluating experimental conclusions

• At the conclusion of a chemical investigation, students evaluate whether experimental results support the initial hypothesis regarding enthalpy of reaction or oxidation of alcohols.

Systematic errors vs random uncertainties

• Random uncertainties cause fluctuations around the mean,
• while systematic errors shift results consistently in one direction, significantly impacting accuracy.
  • (such as heat loss or uncalibrated balances)

Identifying procedural weaknesses

• A thorough evaluation identifies specific procedural weaknesses in apparatus design,
• such as evaporative fuel loss or incomplete combustion when burning liquid alcohols in a spirit burner.

Realistic proposals for improvement

• Suggested modifications must be realistic and scientifically targeted,
• such as employing a copper draught shield, bomb calorimeter,
• or digital temperature logging to minimize heat dissipation.

Random error

• Unpredictable variation causing scatter, reduced by repeats.

Primary alcohol

• An alcohol in which the C–OH carbon is attached to one other carbon.

Improvement

• A specific change that addresses an identified weakness.

Weakness

• A feature of the method that leads to significant error.

Alcohol

• A compound containing –OH with a name ending in -ol.

Combustion

• Burning in oxygen

Limitation

• A factor that restricts the scope within which a conclusion is valid.

Calorimeter

• An insulated container used to measure temperature changes in reactions.

Section 8 of 16Evaluating the hypothesis

Final comment

• Final comment follows from the conclusion and judges the strength of the support.

Strength of support

• Strength of support even if the data support the hypothesis, consider the uncertainties and errors.

Scatter

• Scatter significant scatter around the line of best fit suggests random errors and weakens the support.

Section 9 of 16Systematic errors

Systematic errors

Definition

• Definition flaws in the method or apparatus that make results consistently wrong in one direction.

Heat loss

• Heat loss in calorimetry it makes the measured temperature change smaller than the true value, so the enthalpy change is less exothermic.

Miscalibrated instrument

• Miscalibrated instrument a balance that always reads 0.2 g too high is a systematic error.

Repeats

• Repeats repeating trials does not reduce systematic error.

Section 10 of 16Random errors

Definition

• Definition unpredictable variations in measurements that scatter results around the true value.

Examples

• Examples judging a titration endpoint by eye and fluctuations in reading a burette meniscus.

Reduction

• Reduction taking repeat trials and calculating a mean minimises random error.

Section 11 of 16Weaknesses, limitations and assumptions

Weakness

• Weakness an aspect of the method that causes a significant systematic or random error.
• A glass beaker instead of a polystyrene cup lets heat escape in calorimetry.

Limitation

• Limitation a factor that limits the scope of the conclusion.
• An investigation of only four alcohols cannot support a trend for longer chains.

Assumption

• Assumption a simplification in a calculation that is not perfectly true.
• The specific heat capacity and density of dilute solutions are taken as those of water.
• State the assumption, why it is not fully valid, and how it affects the result.

Section 12 of 16Weakness, impact, improvement

Weakness

• Weakness state the specific problem and whether it is random or systematic.

Impact

• Impact say how the data were shifted or scattered, using your own observations or graphs.

Improvement

• Improvement propose a specific change that addresses that weakness.

Heat loss

• Heat loss add an insulating lid to the calorimeter and a draught shield around the apparatus.

Incomplete combustion

• Incomplete combustion soot shows not all fuel was converted to CO₂ and H₂O,
  • so less energy was released; adjust the wick distance to improve combustion.

Limited range

• Limited range extend the range of the investigation, for example more members of the series or isomers.

Section 13 of 16Making improvements realistic and specific

Relevant

• Relevant the improvement must address the weakness identified.

Realistic

• Realistic it must be possible in a typical school laboratory; a bomb calorimeter is not realistic.

Specific

• Specific refer to your own results, graphs and observations, not a generic evaluation.

No "human error"

• No "human error" identify a specific cause, such as parallax error when reading a meniscus.

Prioritise

• Prioritise focus on the one or two errors with the biggest impact, such as heat loss in calorimetry.

Link to data

• Link to data large error bars at high temperatures suggest timing a fast reaction was difficult, so a light sensor or data logger could be used.

Section 14 of 16More from the specification

More from the specification

Percentage Error Calculation

• Quantifies accuracy by comparing experimental results to accepted literature values: Percentage Error = × 100%.
  • (|v_exp - v_lit| / v_lit)

Concluding Against Research Questions

• A robust scientific conclusion directly addresses the original research question, synthesizing empirical data without over-generalization.

Evaluating Systematic vs Random Uncertainty

• When percentage error significantly exceeds total percentage uncertainty, systematic errors dominate the experiment.
  • (e.g. uninsulated heat loss or concentration inaccuracies)

Contextualising with Literature Sources

• Comparing experimental findings with peer-reviewed literature values allows appraisal of whether the experimental methodology was fundamentally sound.

Concentration

• Moles ÷ volume in dm³, or g/dm³.

Percentage error

• The difference between experimental and literature value as a percentage of the literature value.

Percentage uncertainty

• The absolute uncertainty divided by the measured value, multiplied by 100.

Primary alcohol

• An alcohol in which the C–OH carbon is attached to one other carbon.

Section 15 of 16Key terms

Term	Meaning
Conclusion	A summary answer to the research question based on the evidence.
Hypothesis	A testable prediction with a scientific explanation.
Percentage error	Difference between experimental and accepted value as a percentage of the accepted value.
Percentage uncertainty	Absolute uncertainty as a percentage of the measured value.
Coefficient of determination	R2, a measure of how well a line fits the data.
Literature value	An accepted value from a reliable source.

Term	Meaning
Evaluation	A critical review of the method, its errors, limitations and improvements.
Systematic error	An error that consistently pushes results in the same direction.
Random error	An unpredictable variation that scatters results.
Limitation	A factor that restricts the scope within which a conclusion is valid.
Assumption	A simplification in a calculation that is not exactly true.
Incomplete combustion	Burning with insufficient oxygen, giving CO or soot and releasing less energy.
Improvement	A specific change that addresses an identified weakness.

Section 16 of 16Exam technique

1

Concluding more than the data show, such as claiming a rule for conditions that were not tested.

2

Failing to cite the source of a literature value.

3

Saying a result is "close" to the literature value instead of quantifying the percentage error.

4

Writing a conclusion that never answers the research question.

1

Writing vague points such as "human error" without a specific cause and impact.

2

Suggesting improvements that do not address the stated weakness.

3

Mixing up limitations (scope of the conclusion) with assumptions (simplifications in calculations).

4

Not linking the evaluation to your own graphs and observations.