Students will be able to identify and discuss their own career aspirations or relevant skills and knowledge and how they impact on others.
Data Tables[ edit ] Data should be collected in tables in a systematic way that makes it clear and easy to understand.
Advancing physics practical coursework should make it easy to find the information that is required and should include appropriate units and uncertainty. Reference tables of data may be given in an appendix as they may be long.
Tables in the body of a report should be designed to convey a message clearly and may only include summary data such as averages. The layout and contents of a results table, whether it is for recording numerical data or observations, should be decided before the experiment is performed.
Space should be allocated within the table for any manipulation of the data that will be required. The heading of each column must include both the quantity being measured and the units in which the measurement is made.
Readings made directly from measuring instruments should be given to the number of decimal places that is appropriate for the measuring instrument used for example, readings from a metre rule should be given to the nearest mm.
Quantities calculated from raw data should be shown to the correct number of significant figures. Uncertainty[ edit ] All instruments have a level of uncertainty.
In an experiment the biggest source of uncertainty is the most important to consider and try to reduce. The smallest change it can observe or 'see'. However there may be reasons to be even more pedantic about results.
The results on a meter may flicker randomly or in response to changing conditions like being knocked. Repeated readings of the same experiment may vary. The calibration of the instrument.
Is it giving a true reading compared to other supposedly identical instruments of against a known standard? The uncertainty can be displayed on a graph as an Error Bar.
Systematic Errors[ edit ] Systematic errors can arise from the experimental procedures or other bias.
Zero error on an instrument making all readings too large or small by a set amount A micrometer that reads A set of scales that has not been zeroed first. Calibration of an instrument giving false readings. An ammeter consistently giving reading that are too high.
A measuring tape becoming stretched over years of use. Experimental design flaws Friction on a sloping runway not being accounted for. A resistor changing its value as it gets hot.
Resistance of connecting wires. These will often result in a line of best fit on a graph that doesn't go through an intercept where expected. An experimental design can be improved to try to remove systematic errors. These are often noise or random fluctuations in a repeated reading.
The height a ball bounces to when dropped from the same height. The small variations in voltage when repeating a reading on the same length of wire.
They may also be due to a mistake or human error in the reading, for example using your eyes to measure the height that a ball bounces may lead to an outlier due to an error in judgement.
Human error would be the most likely source of an outlier.
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Spread and identifying possible outliers[ edit ] It is often useful to use plot and look as a quick way to assess the quality of data. This is a dotplot that shows the distribution of a set of data.Physics in Use (10 marks) OCR B Advancing Physics Physics Practical Investigation Learn the art of brilliant essay writing with help from our OCR B Advancing Physics Physics Practical Investigation Coursework Investigating Simple Harmonic Find Coursework Sale – 4, Completed ORDERS Today for Find Coursework Sale – 4, Completed ORDERS.
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