Conclusion/Evaluation (CE) 1. Section 3:Conclusion and Evaluation 2.

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Conclusion/Evaluation (CE) 1

Transcript of Conclusion/Evaluation (CE) 1. Section 3:Conclusion and Evaluation 2.

Page 1: Conclusion/Evaluation (CE) 1. Section 3:Conclusion and Evaluation 2.

Conclusion/Evaluation (CE)

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Page 2: Conclusion/Evaluation (CE) 1. Section 3:Conclusion and Evaluation 2.

Section 3:Conclusion and Evaluation

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Organisation of Conclusion and Evaluation

1.Conclusion – clear, simple, precise statement (s)

2.Explanation of conclusion

3.Evaluation of results

4.Evaluation of the procedure

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ConclusionThe concentration of sucrose affects the rate of osmosis across eggs

The rate of osmosis into a chicken (Gallus Gallus) egg is affected by the concentration of sucrose in which it is immersed. The rate of osmosis into the egg is least at 1 M sucrose, and increases as sucrose concentration decreases from 1 M to 0.2 M.

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Explanation of conclusion1. Explain briefly how your graphs and statistical

analysis support your conclusion

2. Provide references support fro the scientific literature to support your conclusion

3. Refer to your hypothesis (if you made one) and state if it has been supported or refuted

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Critical evaluation of the results

1. How reliable is the data?

2. Do the repeats support each other?

3. Are any uncertainties large enough to have a significant effect?

4. How large is the standard deviation?

5. Can you draw a good line of best fit, or are there alternative lines of best fit?

6. Does the graph match your hypothesis?

7. Explain the results of any statistical analysis 6

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Critical evaluation of the results (2)

EXPLAIN your critical evaluation of the data

Use p. 34 – 35 of your book for inspiration

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Critical evaluation of the procedure

You must use the words ‘accuracy’ and ‘reliability’

Accuracy: correct and careful use of the best available apparatus

Reliability: Having enough data to be able to process it fully and draw firm conclusions

Identify at least 3 clear weaknesses and provide a realistic improvement for each

Identify the weakness and suggest the improvement

before going on to the next weakness

The weakness commonly involves equipment OR methodology

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ConclusionFrom the graph, we can deduce that

the surface area to volume ratio has a strong positive correlation to the degree of penetration. The points lie on a curve of best fit that plateaus near the end.

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Too vague, data not usedNo justification

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Conclusion correctionAdd data

The points lie on a curve of best fit that plateaus after the Surface area/Volume ratio reaches 7.

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Use of data

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Conclusion correctionResearch quote, correctly referenced

“student background information diffusion, osmosis and cell membranes” biology.arizona.edu, last accessed 16.10.2008 13.15.

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Use of research

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Experimental error (example)

Error Estimate of level of error

Possible improvement

The cutting of the gelatin was inconsistent, thus each edge of the shape was of slightly unequal length

± 2 mm 1.Scalpel to replace knife 2.Cut along a set square3.Prepare blocks of exact sizes using moulds

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EvaluationThe errors are not sufficiently large to affect the

line of best fit. However, the operator error in cutting the blocks and reaction time when using the stopwatch……….

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No figures, improvements

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EvaluationThe uncertainty value of 5.56% is acceptable and

the allows a curve of best fit within the error bars.

The operator error in cutting the blocks increases personal uncertainty, this could have been improved by using blocks cast in different sizes instead of cutting

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Suggested improvement

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Uncertainty processing Uncertainty processing is not required but can be done

Uncertainties must be listed in the data and evaluated in terms of their effect on the results and how they could be minimised.

Uncertainty calculations are not required, but the simplest method is to calculate a percentage uncertainty by uncertainty of instrument used

Maximum uncertainty is the uncertainty divided by the smallest measurement

Mean uncertainty is the uncertainty divided by the mean measurement

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Uncertainty calculation example

Length: ±0.5mm (systematic)

Maximum uncertainty: 0.5 mm/9mm x 100% = 5.56%

Mean uncertainty = 0.5/15 x 100% = 3.33%

Time: ±0.005s (absolute)

Uncertainty: 0.005s/600s x 100% = 0.001%

Total maximum uncertainty = 5.56%

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