SKILLS
In this examination Section A is a compulsory question with a number of sub-sections. it requires the organisation and manipulation of a range of data, resource material and information using a variety of skills in an unfamiliar context. (using material based on data collected during real or imaginary fieldwork...river investigation,coastal investigation,weathering or urban/ rural area investigations)
Resources = maps, tabulated data, written text, photographs(ground and aerial), field sketches, sketch-maps, and cross/long-sections.
This tests your knowledge, understanding and application of geographical skills.
thus showing your ability to....
understand the classification of data,
apply and explain the main sampling methods used in the subject -their importance to obtain information about a pop.
use a a variety of presentation techniques and be able to interpret various ones.
compute measures of central tendency or dispersion (variation)
sketch a best fit line and identify anomalies
apply simple statisitcal tests like SRCC and Chi-square
make interpretations (geographically) of a number of resources related to a question or hypothesis.
be able to draw conclusions from data/resoures, and comment on how valid they are
to extend ideas for further investigation.
As a result of Field work you will be expected to be able to
- demonstrate their understanding of
- accurate measurement and sampling
- data handling
- interpretation of both primary and secondary data
- data representation by maps, diagrams or other means
- show an awareness that geographical ideas and methods may lead to a variety of investigations, and that explanations may be partial, tentative or fully formed
- that you can exercise transferable understanding, practical and fieldwork skills from the AS units, to enhance anaysis and critical thinking in an unfamiliar situation.
- draw on their fieldwork investigations and experience
- refer to specific details of their fieldwork
- respond to unfamiliar fieldwork data.
So.... in the examination you will be asked to
- outline the aims and objectives of a fieldwork exercise
- draw on theoretical knowledge to justify a fieldwork exercise
- identify, describe and justify different methods of data collection
- show evidence of observation and practical skills
- recognise a range of factors affecting any fieldwork investigation
- suggest a variety of presentation technigques appropriate to any fieldwork ivestigation
- demonstrate appropriate geographical skills of presentation
- make analytical comment about fieldwork data, showing awareness of other factors influencing that data
- summarise and make logical conclusions from fieldwork data
- demonstrate an appreciation of the limitations of fielwork evidence
- suggest or comment on opprotunities to extend a fieldwork investigation
Resources, skills and techniques applying across all AS units
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Sections of articles and text
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Tabulated data
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Topographical maps
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landuse maps
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Cloropleth and isopleth maps
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Aerial and satellite photographs
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Annotated sketches in the field or from photographs
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Annotated sketch maps
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Line graphs and cummulative line graphs
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Bar charts and histograms
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Pei graphs and divided bars
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Scattergraphs, best-fit lines and/or curves
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Triangular graphs
SAMPLING
Ramdom - all have equal chance of being selected, using diace random number tables,etc. useful where area being surveyed is fairly uniform (Residential area of a town). It weakness is it is subjective and often not completely random.
Systematic - covers the whole area length, points are sampled at regular intervals,especially useful where there is a lot of variation along it's length and you need to have a representative sample of all the changes.Often there can be practical problems like access or landownership(remember the river Chalmerdale fieldwork).
Stratified - to replicate the same structure in the sample, so points are taken to reproduce chnges within the sample, useful when these characteristics can be established like the age/sex profile of a of a town. (prior knowledge is a help here)
Why sample? = smaller amounts of data easier to handle,although it needs to be representative !
What type of sample? = 3 types see above.
What size of sample? = large enough to be representative but not too large to be troublesome, how much times you have , what sort of statistic you are going ti use on this (SRCC = min 10).
Data presentation= line graphs,(continuous data..showing change over time or distance..easy to see trends,but can be difficult to interpret between points) cumulative line graphs,(to show effect of adding to previous frequencies,normal distribution should have an 'S' shape curve, distributions are often skewed and so curve is unbalanced) logarithmic graphs,( can show trends over time and relationships,allows non-linear scales on special graph paper allow a wide range of values to be plotted and allows accuracy at the lower end of the range, but limited accuracy at the upper end of the range) Best- fit line (a line drawn byeye passing as near as possible through all the points on a scattergraph, this highlights anomalies, with predictions of unknown values possible, can be wrongly inferred, should it be a line or a curve) bar charts (quantitative scale, frequency in categories, and enables easy comparision (blocks should be separated) no real disadvantages) histograms,(two quantitative scales, and a continuous honizontal scale,easy to see variations (blocks should be together) ..disadvantage only if equal intervals not used) pie graphs, (shows relative contributions of components to the total, so show relative importance..better than divided bar graphs for more than 4-5 catoegories, actual values are hard to determine) divided bar charts,shows the number of components in a category, good to see changes over time, but difficult to see changes in components, can be better if using %) proportional symbols,/circles (size of symbol equals proportion of total, very visual especially nested ones, can be difficult to construct accurately) flow lines, shows volumes of flow in a given direction using arrows of proportional width or length, so easy to see relative magnitude and direction, especially good when used with maps, best used for one type of information, exact numbers difficult to read but good to give impressions) triangular graphs, (three variables can be shown and their relationship to the total, easy to check as add up to 100% and can see the dominant variable, it can be difficult to work out which axis to read) scatter graphs, (quick and easy way to show relationships,easy to see patterns,independent variable should be on x-axis choropleth maps,(shaded map like physical maps in atlases, shows variation across an area, can see spatial patterns and it's easy to construct, boundaries can be artificial, gradual changes not shown, care must be taken with categories chosen) isopleth maps, (maps constructed with lines joining places of equal value, like temp. maps in atlases, not affected by boundaries and individual points left on as well, lots of data needed however, and can be hard to consdtruct if patterns not obvious and it assumes gradual changes between values).
STATISTICS!
The AS course demands that a number of presentational/statistical techniques have to be developed
- Mean, Median and Mode
- Spearmans' Rank Correlation Coefficient (SRCC)
- Chi-Square test
- Quartiles and interquartile range
- MEAN = the average (it is found by totalling the values in a data set and dividing by the number of items) eg ... 2,4,6,8,10 Total = 30/5 = 6 It is the most commonly used techniques but can be influenced by extreme values.
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- MEDIAN =This is the mid-point of a set of values. The initalprocess is to rank the data set in descending order. A data set with an even number of values has to be treated differently than one with an odd number of values.
- even 1,2,6,7,11 (median- 6)
- odd 1,2,6,4,7,11 (in this example you need to find the mean between the two central values, in this case 6 and 4 =5. The mean in this case is 5 (it is not a value in the data set).
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MODE = The most frequent value in a series eg.... 2,4,6,4,1,3,4,2,4, In this case the mode is 4.
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SPREARMAN'S RANK CORRELation coefficient (SRCC)
- This is a statistical technique which identifies a correlation between 2 variables (eg. changes in temperature and the sales of ice creams ).
- The formula is as follows Rs = 1-6 sum of Dsquared/ n3 -n
- The result in itself does not tell us a lot. You will need to use a table of significance to assess whether it is statistically significant.
- Improtant things to remember about SRCC
- The greater number of paired data sets the better (12-15 as a minimum)
- It is preferable to produce a scatter graph of your results before you undertake theSRCC because this may highlight the fact that there is no correlation between the two varialbes therefore the SRCC may not be appropriate.
- The statstic must be used in conjunction with significance tables (these relate the accuracy to the number of data sets that you have)
- It does not prove causation, only that the result you have obtained is unlikely to have occurred by chance (or not!). For example, you could undertake SRCC on the link between the birth rate of a country and the number of storks!!! This would show you that indeed, as the number of storks increases so does the birth rate, but it does not say that one causes the other.
- CHI-SQUARE = X2 = (observerd frequency - expected frequency)2/expected frequency
- This test allows you to see if there is a link between two variables and whether this link is a result of chance or whether external factors have played a part. is used when you are trying to summarize the intersections of independent and dependent variables and understand the relationship (if any) between those variables. For example, if we wanted to know if there is any relationship between the biological sex of farmers and their shoes, we might select 50 males and 50 females as randomly as possible, and ask them, "On average, do you prefer to wear sandals, sneakers, leather shoes, boots, or something else?" In this example, our independent variable is biological sex. The independent variable is the quality or characteristic that you hypothesize helps to predict or explain some other quality or characteristic (the dependent variable). or the degree of weathering of gravestones of different rock types.
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- Is there a relationship between any two variables IN THE DATA?
- How strong is the relationship IN THE DATA?
- What is the direction and shape of the relationship IN THE DATA?
- Is the relationship due to some intervening variable(s) IN THE DATA??
- At the end of section A ,it is essential that you should beable to suggest how an investigation could be extended..perhaps the collection of further data, use better/different equipment,measure with greater accuracy, use a more appropriate sampling method, take a bigger sample, etc.
Edexcel website with specimen paper....
http://www.edexcel.org.uk/VirtualContent/48430/Specimen_GCE_Geography_A_Unit_2___3.pdf
SECTION B
Is about your fieldwork experiences..so you need to be prepared for questions on one of the following ...
a human field day
a physical field day
your fieldwork techniques, methods used from either of the above.
using questions like ...
Where did you carry out your fieldwork?
What were your aims?
What were your Hypothesis?
How did you carry out your primary data collection?
Did you use sampling? If so what sort and why?
Did you use secondary data? If so what sort and why?
How did you present your data and why did you choose those methods?
What were your conclusions?
Were these conclusions reliable? If not,why not?
How would you improve your work? More data different data?
(remember ... you will need to be able to draw 2 sketch maps ( one for general location...its situation and one with specific sites ..using a larger scale) of where you collected data,annotated sketches of different aspects of your fieldwork.. including scale, north point and clear labels and you should be prepared to annotate these with some explanation... like justifying your sites, etc.