The ISA for Physics What you need to revise. Know your experiment Know the type of equipment you...
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![Page 1: The ISA for Physics What you need to revise. Know your experiment Know the type of equipment you used and why you chose it. Know the name of each piece.](https://reader033.fdocuments.in/reader033/viewer/2022051819/5518c5af550346a61f8b57a1/html5/thumbnails/1.jpg)
The ISA for Physics
What you need to revise
![Page 2: The ISA for Physics What you need to revise. Know your experiment Know the type of equipment you used and why you chose it. Know the name of each piece.](https://reader033.fdocuments.in/reader033/viewer/2022051819/5518c5af550346a61f8b57a1/html5/thumbnails/2.jpg)
Know your experiment
• Know the type of equipment you used and why you chose it .
• Know the name of each piece of the equipment and what it does (measures - if applicable).
• Know the sensitivity of the equipment – that should have been evident in the way you wrote results in the table.
• Know why you chose the number of readings to take.
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Terminology
• Make sure you KNOW all of the words to describe variables etc.– Remember it is the independent variable
that you change by a regular amount (and usually plot on the x-axis)
– Remember it is the dependent variable that you measure as it changes in response to the changes in the independent variable (usually plotted on the y-axis).
– The control variables are kept constant to make the results valid.
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Why are control variables kept constant?
– If that variable had changed as well as the independent variable the dependent variable would have responded to that change too – making the experiment invalid. Do not simply say – ‘to make it a fair test’ if asked to explain why control variables are kept constant – expand on the idea… and say it would affect the dependent variable.
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• If you are asked ‘what you were trying to find out’ or the ‘purpose of your investigation’…. they want to know what you decided to investigate.
• They want you to describe how you decided on varying your independent variable and observing the effect this has on the dependent variable…
• They want a brief description of the ‘fair test’ you carried out…
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Minimising errors
• A good experimenter checks the equipment is reliable before beginning – she looks for ‘zero error’ on instruments and calibration errors and uses instruments of a suitable precision.
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Minimising errors
• Zero errors can sometimes be adjusted manually – otherwise they can be noted and deducted from all readings. A column of actual readings should be recorded and then a column of readings corrected for zero error should be drawn.
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Minimising errors
• Calibration errors are a bigger problem.• They can mean that all of the results are out
by a percentage because two fixed points have not been fixed correctly.
• You can spot drastic calibration errors by checking meters against each other – but you don’t know the whole batch may be wrong!
• If you were doing an important research project you would check the meters against standard resistors etc. to see whether they were properly calibrated.
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Minimising errors
• Using instruments with sensitive scales (small divisions – more significant figures) give results with more precision.
• This will not make your results more reliable or accurate (valid) – just more precise.
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Minimising errors
• Any possible causes of errors spotted while carrying out the experiment (sparking, heating, fluctuations in the meters) are noted.
• A repeat set of readings is taken to check the reliability of the first set… any that differ widely on repeating must be checked again.
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How can you tell if your readings are reliable?
• When repeated the results are virtually the same – giving you an average that barely differs from either set.
• When plotted a smooth curve or straight line is obtained – no obvious anomalies – they make a pattern.
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Is reliable the same as accurate?
• NO!!!• If there is a problem with the
accuracy of your measuring instruments and/or an error in how you are using the equipment you will get repeatable data that is wrong.
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Conclusion
• State the findings in terms of how the independent variable affected the dependent one.
• Refer to the graph shape to describe the relationship and make a conclusion from that.
• Does it go through the origin?• Is it the same in negative bias as forward bias?• Does it indicate direct proportionality?• If you can use numbers do so!
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Evaluation
• Are your results valid for ALL components or only true for the one you did?
• In order to make a more general conclusion how many others would you have to test?
• Would you expect all of the results to be identical?
• What tolerance would you allow?