Analysing and interpreting the evidence
This section is usually done under conditions of high control. Make sure you understand from your teacher what you are allowed to do during this time. You will need to think through what the results are suggesting.
When analysing and interpreting your research findings, make sure that you:
- Structure your writing so that your interpretation is set apart from the findings. It is important that your interpretation is clearly labelled as separate from your research.
- Present your analysis clearly and concisely.
- Think about how your interpretations relate to one another. Do they shed light on a particular geographical trend? Do your results prove or disprove any hypotheses [hypotheses: An initial, tentative theory which is then tested to see if it fits the facts. ] you have set out to test at the beginning of your research?
- You will gain marks for demonstrating a clear understanding of geographical themes, as well as a body of factual knowledge.
Evaluation and conclusion
- Being able to evaluate the strengths and weaknesses of your work is a vital part of any geographical research.
- If you had more time, how would you further your research?
- Did you come across any problems with the data collection?
- Were there any aspects of your research that could skew your final conclusions?
- How do you think your own thoughts and opinions could influence your findings?
- Showing you are able to review your research from a critical distance is important.
- When writing up your conclusions, do not be afraid to bring up new ideas and thoughts you may have about your research project. You will gain marks by showing you have and can use your own original ideas.
Ask your teacher to show you examples of past students' work. It's useful to see a range of different levels of work to evaluate why one gained more or less marks than another. This can help you focus on what you need to do in order to get a high grade for your own research.
However, do not be tempted to copy or download work from internet sites. Plagiarising (copying) another person's work could have serious repercussions. Make sure the work is your own.
Back to Geographical skills index
Go back through each one of your methods. For each, consider
- How accurate were your results?
- What were the sources of error?
- How has each source of error affected your results?
True value: the value that would be obtained in an ideal measurement
Accuracy: how close a measurement is to the true value
Error: the difference between the result that you found and the true value
What are the sources of error?
- Measurement error: mistakes made when collecting the data (such as someone misreading a clinometer)
- Operator error: differences in the results collected by different people (such as different people giving different environmental quality scores)
- Sampling error: where a sample is biased. Some elements of the population are less likely to be included than others.
Validity: the suitability of the method to answer the question that it was intended to answer
How do sources of error affect results?
Suggest how errors could have changed the results. Here is an example.
|Fieldwork technique||Questionnaires were given out to every 5th person seen in the High Street on Sunday morning|
|Bad evaluation||It was raining heavily when I gave out questionnaires|
|Good evaluation||It was raining heavily when I gave out questionnaires, so there were few people in the High Street except for rough sleepers. My sample was biased because shoppers were under-represented. Therefore the results of the questionnaire survey may not be accurate.|
Random error: these cause results to be spread about the true value. For example, imagine a student takes 20 temperature readings and mis-reads the thermometer for 2 of the readings. The effect of random errors can be reduced by taking more measurements.
Systematic error: these cause results to differ from the true value by a consistent amount each time the measurement is made. For example, imagine a student uses weighing scales which have not been zeroed, so all the results are 10g too high. The effect of systematic errors cannot be reduced by taking more measurements.
These are values in a set of results which are judged not to be part of the variation caused by random uncertainty.