Numerical Skills

When designing your fieldwork, you need to be able to design data collection sheets before you start. An example of this would be if you were studying water flow at the edge and in the centre of a stream. A suitable table would include a column for the distance from the starting point of your survey with two columns for flow rate, one for the edge and the other for the centre. Data collection sheets can be modified if you don't get them quite right, but you will be required to explain why you changed them in your evaluation. You won't lose marks but you could easily gain them for doing that. Your planning also needs to show that you appreciate ways of ensuring that your data is as accurate and reliable as possible for example, repeat readings or comparing with a control group as appropriate.

When processing numerical data, you will need to use a number of valid statistical techniques, including appropriate measures of central tendency, spread and cumulative frequency (in other words - median, mean, range, quartiles and inter-quartile range, mode and modal class). Being able to work out and use percentiles, percentage increases and percentage decreases is essential, but once you get the hang of it, it's not actually too difficult. At the highest levels, you need to be able to spot weaknesses in selective statistical presentation of data.

Finally, when processing bivariate data (that's the posh way of saying data that includes two variables), not only should you be able to identify and draw trend lines on a graph, you should be able to work out gradients and use the trend lines to describe any correlation between data sets and extrapolate and interpolate the trends you have identified. But don't get too stressed about this, you will already have done loads of this in maths and science lessons as well.