Analysing findings, and the conclusion
Describing is not analysing, and Level 3 asks for the second
- At Level 2 (AS91244) you explain your findings. At Level 3 you analyse them, and at Excellence you critically analyse them. The verbs are the difference.
- Describing = nitrate rose from 1.2 mg/L at S1 to 8.9 mg/L at S4.
- Explaining = it rose because the pasture reach adds nitrogen through runoff.
- Analysing = the rise is not steady: it is steepest through the pasture reach at about 1.9 mg/L per kilometre and flat below the township, which means the input is distributed along the reach rather than entering at a point.
- Critically analysing adds the question of what else the data could mean, and how confident you are entitled to be.
A structure for the analysis section
- State the pattern, with figures and units.
- Quantify the rate, not just the endpoints — per kilometre, per visit, per land-use reach.
- Relate it to the spatial variable, because that is what makes it geography.
- Bring in a geographic concept and apply it: pattern, process, interaction, change, sustainability.
- Say what the data cannot show, which is where the critically comes in.
Making the analysis geographic
- The standard requires you to explain findings incorporating the relevance of geographic concepts. Name the concept and attach it to your own data.
- Process — a sequence of actions producing your result: runoff carrying nitrogen from pasture to channel during and after rain.
- Pattern — the spatial arrangement your map shows: rising downstream, steepest in the middle reach.
- Interaction — people and the environment affecting each other: stock access at S3 breaks the bank, which raises turbidity, which reduces clarity, which affects the invertebrates the river's health is judged on.
- Sustainability — whether the current use can continue without preventing future use, which is a question your data can inform but not settle.
- Do not define the concepts. Apply them to your numbers.
Using every part of your dataset
- Analyse the exceptions, not just the trend. In the invented study, clarity falls sharply at S3 and only partly recovers, while nitrate keeps rising — two variables behaving differently is a finding, because it suggests two different mechanisms.
- Use the repeat visits. Identical site rankings on four days is evidence about reliability and belongs in the analysis, not only in the evaluation.
- Use the photographs and the sketch. They explain mechanisms the numbers can only show the effect of.
- Use the secondary data for context. Rainfall records confirming four dry antecedent periods is what allows you to compare the visits at all.
- Do not leave a variable unanalysed. If you measured flow, say what it showed — even if the answer is that it was too imprecise to use.
Writing a conclusion that answers the aim
- The conclusion must relate to the aim, and markers check the pairing directly. Put the aim and the conclusion side by side before you submit.
- Answer each focusing question in order, in a sentence each, with a figure.
- State the confidence you are entitled to. Nitrate rises downstream and rises fastest through the pasture reach is supported; pasture causes the rise is not, because distance and land use are confounded in this catchment.
- Use "associated with" where you cannot show causation, and say why you have chosen the weaker word. That sentence often earns more than the finding itself.
- Do not introduce new data in the conclusion, and do not put the evaluation there — it is its own section.
Worked Example
Worked example
Analyse these findings from the invented Rerenga study, then write the conclusion.
Mean nitrate (mg/L): S1 1.2, S2 3.4, S3 5.1, S4 8.9, S5 8.4. Mean clarity (cm): S1 92, S2 78, S3 41, S4 46, S5 55. Site spacing about 3 km. Land use: S1 forest; S2, S3 pasture; S4 below township; S5 river mouth.
Answer:
Step 1 — state the pattern with figures.
Nitrate rises from 1.2 mg/L at S1 to a maximum of 8.9 mg/L at S4, a 7.4-fold increase over about 12 km, then falls slightly to 8.4 mg/L at S5.
Step 2 — quantify the rate, which is where analysis begins.
The rise is not uniform. Between S1 and S2 it is about 0.7 mg/L per km; between S2 and S4 about 1.4 mg/L per km; between S4 and S5 it is negative. The steepest section is the pasture reach.
Step 3 — analyse the second variable, because it behaves differently.
Clarity does not mirror nitrate. It falls steadily to a minimum of 41 cm at S3, then improves at S4 and S5 while nitrate is still high. Two variables with different spatial patterns cannot have the same cause. Clarity is responding to something local at S3 — the photographs show stock access and a bare bank there — while nitrate is responding to something distributed along the whole pasture reach.
Step 4 — apply a geographic concept to your own data.
This is process and pattern together. A point-source process produces a step in the data at one site and recovery afterwards, which is what clarity does. A diffuse process produces a steady gradient along a reach, which is what nitrate does. The shape of each curve identifies the kind of process behind it.
Step 5 — state what the data cannot show.
Distance downstream and land use change together in this catchment, so the data cannot separate land use causes nitrate from nitrate accumulates downstream. The S5 fall is within the error of my flow measurement, so dilution and in-stream processing cannot be distinguished.
Step 6 — write the conclusion, answering the aim clause by clause.
The aim was to investigate how nitrate and clarity in the Rerenga vary with distance downstream and with adjacent land use, over four days in March.
Nitrate rises with distance downstream, from 1.2 mg/L at S1 to 8.9 mg/L at S4, and the rise is steepest — about 1.4 mg/L per km — through the pasture reach.
Clarity does not follow the same pattern: it reaches a minimum of 41 cm at S3 and partly recovers downstream, which indicates a local rather than a distributed source.
Across the four days, the ranking of the five sites was identical every time, so the spatial pattern is stable under the flow conditions sampled.
On land use, the highest nitrate concentrations are associated with the pasture and township reaches. I use "associated with" rather than "caused by" deliberately: in this catchment distance downstream and land use change together, so my design cannot separate them.