1. The ISA for Physics
What you need to revise

2. 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.

3. 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.

4. 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.

5. 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…

6. 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.

7. 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.

8. 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.

9. 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.

10. 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.

11. 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.

12. 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.

13. 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!

14. 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?