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Analysis Intro
 

Analysis Intro

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    Analysis Intro Analysis Intro Presentation Transcript

    • Analysis and Conclusions Mark Scheme – Top Band (14-18 marks for analysis and interpretation) The student produces and effective, coherent and independent analysis and interpretation which draws upon all the information collected and presented, and is directly related to the stated aims. Significant interrelationships and patterns are identified and developed. Statistical analysis and significance testing are used accurately and when appropriate. Where group data collection forms part of the enquiry, there is clear evidence of individual analysis. A good range of appropriate geographical terminology is used, and there are few, if any, errors in grammar, punctuations or spelling.
      • In brief then, you need to….
      • Look for spatial / temporal patterns which are clearly linked to the data
      • Explain or attempt to interpret the patterns using your data to back this up and also try and relate back to your geographical theory
      • Ensure you answer all of your key questions
      • Use statistical tests correctly – link your findings into your discussion
      • Use good geographical terminology (would be useful to include a glossary at back of project
      • High standards in grammar, punctuation and spelling are essential!
    • Structuring your Analysis
      • Take each of the questions from your proposal form in turn:
      • Produce graphs of the relevant data to look for relationships or to identify patterns (as suggested in question)
      • For your graphs:-
          • Explain what should happen (according to theory)
          • What do your graphs actually show? – pick out figures to quote
          • Identify any anomalies – attempt to explain them
          • Does it match what you expect? What is it the significance of this
          • If it doesn’t match what you would expect try and explain / suggest reasons why..
      • 3 . If you are comparing two sets of data you can carry out a statistical test such as Spearman to test the relationship between the two sets of data. (make sure you state your null and H 1 hypothesis and set out your interpretation of your results.
    • Spearman’s Rank Correlation Co-efficient:
      • Remember to always state your null hypothesis (H o ) and alternative hypothesis (H 1 )
      • Calculate your Spearman Correlation Co-efficient (R) – interpret the value – e.g.
      • A correlation coefficient of R of 0.85 suggests a strong positive correlation .
      • You then need to test the statistical significance of the relationship using the significance table. E.g. if at n=12 the R is greater than the significance level at the 99% confidence level, then it tells as that the relationship shows a strong positive relationship which is over 99% statistically significant.
      • E.g. If R = 0.85 and at the 99% confidence level the figure is 0.65 R is greater than this so it is over 99% statistically significant.