1.1  Practical skills assessed in the written examination

1.1.1  Planning

Learners should be able to demonstrate and apply their knowledge and understanding of:

(a) experimental design, including to solve problems set in a practical context Including selection of suitable apparatus, equipment and techniques for the proposed experiment. Learners should be able to apply scientific knowledge based on the content of the specification to the practical context.

(b) identification of variables that must be controlled, where appropriate

(c) evaluation that an experimental method is appropriate to meet the expected outcomes

1.1.2  Implementing

(a) how to use a wide range of practical apparatus and techniques correctly as outlined in the content of the specification and the skills required for the practical endorsement.

(b) appropriate units for measurements

(c) presenting observations and data in an appropriate format.

This means draw a results table.  You should be able to do this by now.  Don't forget units in every column heading, even those for data that you have calculated not measured.

1.1.3  Analysis

Learners should be able to demonstrate and apply their knowledge and understanding of:

(a) processing, analysing and interpreting qualitative and quantitative experimental results Including reaching valid conclusions, where appropriate.

(b) use of appropriate mathematical skills for analysis of quantitative data Refer to Section 5d for a list of mathematical skills that learners should have acquired competence in as part of their course.

(c) appropriate use of significant figures

This is a mine field.  In general, you should work to the same number of significant figures as the lowest you have on the data.  e.g. if you measure a length to three sig fig and a mass to two sig fig, your final result can only be quoted to 2 sig fig.  In questions, you should use the same number of significant figures as the data in the question was given.

(d) plotting and interpreting suitable graphs from experimental results, including

(i) selection and labelling of axes with appropriate scales, quantities and units

(ii) measurement of gradients and intercepts.

1.1.4  Evaluation

Learners should be able to demonstrate and apply their knowledge and understanding of:

(a) how to evaluate results and draw conclusions Learners should be able to evaluate how the scientific community use results to validate new knowledge and ensure integrity.

(b) the identification of anomalies in experimental measurements

Nothing much new to say here, an anomalous result is still one that does not fit the trend.  You should ignore them in the calculation of the mean and circle them on a graph and ignore them when drawing a line of best fit.

(c) the limitations in experimental procedures

You should be able to discuss what you can and can't prove with your experiment.

(d) precision and accuracy of measurements and data, including margins of error, percentage errors and uncertainties in apparatus

This is the big one.  We will do a lot on this and you will get used to it, although it can seem a little confusing at first.

(e) the refining of experimental design by suggestion of improvements to the procedures and apparatus.

Any experiment can be improved.  You should always be considering this when you are doing an experiment.  What problems am I having in getting accurate results.  What could I do about it?