It is very important to understand the difference between experimental errors and 'mistakes'. A mistake is something that you do incorrectly, such as misreading the scale on a thermometer, or taking a reading at the wrong time, or not emptying a graduated pipette fully. Do not refer to these types of mistake when you are asked to comment on experimental errors.
You've already seen, on post # 70 , that every measuring instrument has its own built-in degree of uncertainty in the values you read from it. You may remember that, in general, the size of the error is half the value of the smallest division on the scale.
Errors can also occur if there were uncontrolled variables affecting your results. For example, if you were doing an investigation into the effect of leaf area on the rate of transpiration, and the temperature in the laboratory increased while you were doing your experiment, then you can't be sure that all the differences in rate of transpiration were entirely due to differences in leaf area.
Systematic and random errors
Systematic errors are ones that are the same throughout your investigation, such as intrinsic errors in the measuring instruments you were using.
Random errors are ones that can differ throughout your investigation. For example, you might be doing an osmosis investigation using potato strips taken from different parts of a potato, where perhaps the cells in some parts had a higher water potential than in others. Or perhaps the temperature in the room was fluctuating up and down.
Spotting the important sources of error
You should be able to distinguish between significant errors and insignificant ones. For example, a change in room temperature could have a significant effect on the rate of transpiration (Investigation 4) but it would not have any effect at all on the number of stomata on the upper and lower surface of a leaf (investigation 3).
Another thing to consider is how well a variable has been controlled. If you were doing an enzyme investigation using a water bath to control temperature, then you should try to be realistic in estimating how much the temperature might have varied by. If you were using a high-quality, electronically controlled water bath, then it probably did not vary much, but if you were using a beaker and Bunsen burner then it is likely that temperature variations could indeed be significant.
Tips
During your course:
• Every time you do an investigation, work out and write down the uncertainty in all the types of measurement that you make.
• Every time you do an investigation, think carefully about any errors that may be die to lack of control of variables - which ones might genuinely be significant!
Inthe exam:
• If you are asked about an investigation that seems familiar. It is tempting just to try to recall what the main errors were in the investigation that you did before. This is not a good idea, because the investigation in the exam may not be quite the same. Always think about the actual investigation in the examination question, and think through what the significant sources of error are.
Suggesting improvements
You may be asked to suggest how the investigation you have just done, or an investigation that has been described, could be improved. Your improvements should be aimed at getting more valid or reliable results to the question that the investigation was trying to answer - do not suggest improvements that would mean you would now be trying to answer a different question. For example, if you were doing an investigation to investigate the effect of leaf area on the rate of transpiration, don't suggest doing something to find out the effect of the wind speed on the rate of transpiration.
The improvements you suggest could include controlling certain variables that were not controlled, or controlling them more effectively. For example, you may suggest that the investigation could be improved by controlling temperature. To earn a mark, you must also say how you would control it, for example by placing sets of test-tubes in a thermostatically controlled water bath.
You could also suggest using better methods of measurement. For example, you might suggest using a colorimeter to measure depth of colour, rather than using your eyes and a colour scale.
It is almost always a good idea to do several repeats in your investigation and then calculate a mean of your results. For example, if you are measuring the effect of light intensity on the rate of transpiration, then you could take three sets of readings for the volume of water taken up by your leafy shoot in one minute at a particular light intensity. The mean of these results is more likely to give you the true value of the rate of transpiration than anyone individual result.
Tips
During your course:
• If time allows, try to do at least two (and possibly three) repeats when you do an investigation.
• As you do an investigation, be thinking all the time about how reliable or accurate your measurements and readings are. Think about what you would like to be able to do to improve their reliability or accuracy.
In the exam:
• Be very precise in suggesting how you could improve the investigation - for example, don't just say you would control a particular variable, but say how you would control it.
You've already seen, on post # 70 , that every measuring instrument has its own built-in degree of uncertainty in the values you read from it. You may remember that, in general, the size of the error is half the value of the smallest division on the scale.
Errors can also occur if there were uncontrolled variables affecting your results. For example, if you were doing an investigation into the effect of leaf area on the rate of transpiration, and the temperature in the laboratory increased while you were doing your experiment, then you can't be sure that all the differences in rate of transpiration were entirely due to differences in leaf area.
Systematic and random errors
Systematic errors are ones that are the same throughout your investigation, such as intrinsic errors in the measuring instruments you were using.
Random errors are ones that can differ throughout your investigation. For example, you might be doing an osmosis investigation using potato strips taken from different parts of a potato, where perhaps the cells in some parts had a higher water potential than in others. Or perhaps the temperature in the room was fluctuating up and down.
Spotting the important sources of error
You should be able to distinguish between significant errors and insignificant ones. For example, a change in room temperature could have a significant effect on the rate of transpiration (Investigation 4) but it would not have any effect at all on the number of stomata on the upper and lower surface of a leaf (investigation 3).
Another thing to consider is how well a variable has been controlled. If you were doing an enzyme investigation using a water bath to control temperature, then you should try to be realistic in estimating how much the temperature might have varied by. If you were using a high-quality, electronically controlled water bath, then it probably did not vary much, but if you were using a beaker and Bunsen burner then it is likely that temperature variations could indeed be significant.
Tips
During your course:
• Every time you do an investigation, work out and write down the uncertainty in all the types of measurement that you make.
• Every time you do an investigation, think carefully about any errors that may be die to lack of control of variables - which ones might genuinely be significant!
Inthe exam:
• If you are asked about an investigation that seems familiar. It is tempting just to try to recall what the main errors were in the investigation that you did before. This is not a good idea, because the investigation in the exam may not be quite the same. Always think about the actual investigation in the examination question, and think through what the significant sources of error are.
Suggesting improvements
You may be asked to suggest how the investigation you have just done, or an investigation that has been described, could be improved. Your improvements should be aimed at getting more valid or reliable results to the question that the investigation was trying to answer - do not suggest improvements that would mean you would now be trying to answer a different question. For example, if you were doing an investigation to investigate the effect of leaf area on the rate of transpiration, don't suggest doing something to find out the effect of the wind speed on the rate of transpiration.
The improvements you suggest could include controlling certain variables that were not controlled, or controlling them more effectively. For example, you may suggest that the investigation could be improved by controlling temperature. To earn a mark, you must also say how you would control it, for example by placing sets of test-tubes in a thermostatically controlled water bath.
You could also suggest using better methods of measurement. For example, you might suggest using a colorimeter to measure depth of colour, rather than using your eyes and a colour scale.
It is almost always a good idea to do several repeats in your investigation and then calculate a mean of your results. For example, if you are measuring the effect of light intensity on the rate of transpiration, then you could take three sets of readings for the volume of water taken up by your leafy shoot in one minute at a particular light intensity. The mean of these results is more likely to give you the true value of the rate of transpiration than anyone individual result.
Tips
During your course:
• If time allows, try to do at least two (and possibly three) repeats when you do an investigation.
• As you do an investigation, be thinking all the time about how reliable or accurate your measurements and readings are. Think about what you would like to be able to do to improve their reliability or accuracy.
In the exam:
• Be very precise in suggesting how you could improve the investigation - for example, don't just say you would control a particular variable, but say how you would control it.
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