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Interpreting data

Interpreting data. Our field and lab work has generated a large data base What do these data mean? This session- explore how to critically evaluate our own results Ideally- apply statistical methods to the analyses- but unlikely that we would have enough data.

vivien-wade
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Interpreting data

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  1. Interpreting data Our field and lab work has generated a large data base What do these data mean? This session- explore how to critically evaluate our own results Ideally- apply statistical methods to the analyses- but unlikely that we would have enough data

  2. Example 1- Comparing results from duplicate sampling points Hole 1 Sediment Hole 2 Bedrock 234 ppm Pb 456 ppm Pb • What could we conclude? • Both samples showed Pb was present. • A mean value of 345 is a fair • representation of Pb levels.

  3. Example 1- Comparing results from duplicate sampling points • Also gives a mean of 345 ppm, • but the distribution of Pb in the sediment is highly variable. • More variation : need more sample holes • Supposing we do 6 samples and get 0,0,0,0,0,0, 2070? • Is a mean value of 345ppm a sensible way of conveying [Pb]? Hole 1 Sediment Hole 2 Bedrock 0 ppm Pb 690 ppm Pb

  4. Can different analyses results be true? Hole 1 Sediment Hole 2 Bedrock [Pb] Mean Actual variation in [Pb] at base of sediment • It is entirely reasonable to expect variation • in the results • This variation may be due to the • sedimentary environment

  5. Comparing results between sites 2 1 4 3 5 Our original site • Large, reproducable increase in [Pb] between sites 2 and 3. • Progressive decrease in [Pb] downstream from point 3. • Internal variation << external variation.

  6. Second scenario • Means - similar to first scenario • Do we have as much confidence in what • the means say? • Internal variation> external variation • What can we say? • Probably a large effect • A suggestion of decay • Faced with these results what can you do?

  7. Cross referencing with your field notebook • Your field notebook contains a record of what you actually did. 2 m Samples • Be honest with your field notebooks !

  8. What constitutes a ‘result’ • Would it be correct to say that [Pb] @1 >[Pb] @2? • What can we say about the general trend? • Typical of real data: • ‘big ‘ result is evident • Subtle differences absent • May well be true- use the field notebook

  9. Concluding remarks Always critically evaluate your data. • Look at all the data in the light of other information, both the complete data set, and site descriptions • The scientific process utilises field procedures designed to minimise errors • observational skills which facilitate interpretation of the data set

  10. Summary chart Field techniques Field recording/ observations Data Interpretation

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