Biology ISA - Section 2

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  • The results could be useful to people who design drug delivery patches
  • They will know thatas the concentration increases the rate of diffusion increases
  • If they put a high concentration of drug into a patch the difference in in concentration is greater so the rate of diffusion is faster
  • This would be good for painkiller
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Sketch Graphs

Independent variable on the x axis.

Dependent variable on the y axis.

Boths axis need titles and units.

Do NOT draw points, only draw a line of best fit.

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Case Studies

  • Include data
  • Check if the experiment has been repeated
  • Look out for anomalies - have they been included in the mean?
  • Is there a different independent variable?
  • Possitive or negative correlation
  • Is the effext proportional?
  • Does the effect level out? (E.g. a curved line like limiting factors in photosynthesis)
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Suggest why others might get different results

  • They may have used a different method
  • For example they could have used different values for their control variables.
  • Also, they may have used a stronger alkali in the agar cubes which would have made the time taken for the cube to go colourless longer
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Anomalous Results

  • Yes I did get anomalous results
  • They were at 0.4M and 0.6M
  • They are not close to the line of best fit and do not follow the pattern
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Independent Variable & Range

  • Independent Variable - Concentration of acid
  • Range - 0.2M to 1.0M
  • This was a suitble range because there was a difference between the lowest concentration (0.2M) and the highest (1.0M)
  • So my results agree with my hypothesis
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Repeated Readings

  • Discard anomalous results
  • Add the results together
  • Divide the sum by how many results there are
  • This is how a mean value is calculated
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Supporting The Hypothesis

  • Yes my results do support my hypothesis
  • As concentration of acid increases the rate of diffusion increases. The effect is less at higher concentrations
  • For example, with 0.2M of acid the time taken to decolourise was 231 seconds, whereas when this was increased to 1.0M the tim take to decolourise was only 117 seconds
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  • Difficult to decide when all the colour has gone
  • Use the same person to judge the end point
  • This will reduce random errorsand allows you to directly compare the cubes
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  • Compare with others who used the same independent variable
  • Compare to see if they are similar
  • If they are similar then the results are reproducible
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