Essential idea: Scientists aim towards designing experiments that can give a "true value" from their measurements, but due to limited precision in measuring devices, they often quote their results with some form of uncertainty.
Understandings: Error bars; Uncertainty of gradients and intercepts
Applications and skills: Explaining how random and systematic errors can be identified and reduced; Determining the uncertainty in gradients and intercepts
Guidance: Analysis of uncertainties will not be expected for trigonometric or logarithmic functions in examinations (but maybe dealt with in labs)
Data booklet equations: None
Oxford Physics: pages 11 - 14, with good worked examples
Hamper HL (2014): pages 8 - 24. Hamper goes through this topic in a slightly different path than I do, but those pages are a comprehensive look at this whole topic.
Hamper SL (2014): pages 8 - 24. Hamper goes through this topic in a slightly different path than I do, but those pages are a comprehensive look at this whole topic.
pages 16 - 18