Students receive 9 lessons per fortnight, delivered by two different teachers. The course is entirely examined by three written examinations in the summer of Year This course is for A level students only.
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To gain 8 marks, your risk assessment needs to be a separate appendix, which can be completed using a proforma. These can be found all over the internet, but a good one can be found here.
Collecting Data - C - range and quality of primary data. This is easy to get good marks in. You need to collect a good range of data, justifying your choice of range talk about your preliminary work and have a good amount of repeats.
H ighlight your outliers and repeat them. Record everything you measure in a pretty table with all your labels and units and you're all sorted. Analysis - A - revealing patterns in data Another easy section to get full marks in, if you take your time and concentrate. You need to draw a scatter graph of your average results, including a line of best fit.
Depending on your results, this will either be a straight line with a ruler or a smooth curve. This will show you how reliable your data is, as the smaller the error bar, the closer together and more reliable your repeats are. If you have put multiple sets of data onto one graph to show comparisons, you need to make sure that each data set is easily identified and there is a key to show which data is which.
Evaluation - Ea - evaluation of apparatus and procedures. For this section, you need to describe limitations caused by your techniques and equipment. Talk about what problems you might have encountered not necessarily ones that actually happened, just what might have happened and explain what you could do to improve your work the next time.
Think about better, more precise equipment, like electronic timing devices, laser measures and super accurate pipettes. You can also use the section to discuss alternative methods that are available that can provide the same results with more accuracy.
You need to say, for each point, why they would be an improvement. This has to be done in detail to get the top marks. If it helps, you can add diagrams or photographs of the alternative equipment. You can also justify why your method is the best one and that there are no realistic ways to make it any better. Evaluation - Eb - evaluation of primary data.
Identify any outliers you had in your results. You need to talk about the general scatter of your results. Are they close together or far away? What dies this mean about the accuracy of your results?
You also need to refer to your error bars. Small error bars mean increased reliability as all your repeats are close together. Why might your error bars for some points be big while others are small? What might have happened for this to be the result?
Think about all the errors that could have occurred and link this back to the limitations of your method and apparatus. Look at each point individually and say if it is accurate and reliable. Link your decision to the error bars and the distance from the line of best fit.
Review - Ra - collection and use of secondary data. You need to collect secondary data that is relevant to your investigation. Choose people that have done the same experiment as you. Take their hypothesis and results and find, in detail, similarities and differences between your work. Look at their scatter and error bars, as well as where their graph crosses the x axis.
Explain and describe the differences and similarities in all the data.
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