Fieldwork and skills, Year 11: analysing data and evaluating an enquiry

An anomaly (also called an outlier)

HintOn a scatter graph it is the point sitting far from the line of best fit.

The whyOn a graph it stands apart from the trend. It may come from a mistake in measuring or recording, or it may be real and have a local cause, such as a weir that slows a river at one site. AQA asks you to identify these odd results in fieldwork data and comment on them.

Look for a cause, such as a measuring error or something unusual at the site

HintAsk why it happened before asking whether to keep it.

The whyIf the odd result was a slip, such as a misread ruler, it can be left out and the reason stated. If the place really was different, the result is evidence and should stay, with an explanation. Either way the analysis must mention it: quietly removing awkward results is not honest.

describe

HintIt says what happened but gives no reason.

The whyTo describe is to say what the data shows: the pattern, with figures quoted. To explain is to give the reason, using geography: "because pebbles are worn down by attrition as the river carries them". A full analysis does both, and the second step usually begins with "because" or "this is due to".

Less traffic goes with better environmental quality

HintSay how one value moves as the other one moves.

The whyLinking data sets means using one set of results to help make sense of another. Here the two change in opposite directions, a negative relationship, which a scatter graph would show. The link suggests traffic may be a cause of poor quality (noise, fumes), but other things also change with distance, so it does not prove it.

Their sizes are much more varied

HintThe middle half of one sample is squeezed together; the other is stretched out.

The whyAn average alone hides the spread. The inter-quartile range is the spread of the middle half of the values, so a large one means a wide mix of sizes: the sediment at site B is poorly sorted. Choosing a statistic that fits the question, and saying what it shows, is part of the analysis.

Accurate

HintAn archer who hits the bullseye has this quality.

The whyHow close a result is to the truth depends on the equipment and how carefully it is used: a tape pulled tight, a stopwatch started on time, a ruler read at eye level. In an evaluation, say which measurements may have been off, in which direction, and how that would change the results.

Reliable

HintGetting the same answer again says nothing about whether the answer is true.

The whyResults that come out much the same when the method is repeated can be trusted not to be a fluke. That is a separate question from whether they are close to the truth: a pupil who always misses people walking behind a bus shelter would be consistent and consistently too low. (In science lessons this is called being repeatable.)

It is subjective: the score depends on personal opinion

HintAsk whose view each number really measures.

The whySome methods measure (a tape, a counter); others ask for a judgement. Judgements differ from person to person, so the data is less reliable. Improvements include agreeing a description for each score beforehand, having the same person score every site, or averaging several people's scores.

Secondary data, such as past flow records

HintSomeone else has been measuring for decades.

The whyOne of the four things AQA asks for in an evaluation is other data that would have helped. Fieldwork is a snapshot of one day. Published records, old maps and photographs, and official statistics can add the long view and a wider area, and can be used to check whether your own results were typical.

Tentative

HintIt begins like the word for a shelter of canvas.

The whyAn evaluation ends by judging how far the conclusion can be trusted. That depends on the method (was it accurate and fair?) and on the data (was there enough, and was it typical?). With few sites and odd results, the honest wording is "the data suggests" and not "this proves", followed by what would make it firmer.