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Engineering geology of British rocks and soils Mudstones of the ...

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Table 6.3 Stratigraphical subdivisions for Areas 1, 3 <strong>and</strong> 8.<br />

AREA 1 LKM Lower Keuper Marl<br />

MKM Middle Keuper Marl<br />

LKSB Lower Keuper Saliferous Beds<br />

UKSB Upper Keuper Saliferous Beds<br />

AREA 3 TwM Twyning Mudstone Formation<br />

Eld Eldersfield Mudstone Formation<br />

AREA 8 Cbp Cropwell Bishop Formation<br />

Edw Edwalton Formation<br />

Gun Gunthorpe Formation<br />

HlyHollygate S<strong>and</strong>stone<br />

Rdc Radcliffe Formation<br />

Snt Sneinton Formation<br />

caused by depth, <strong>and</strong> o<strong>the</strong>r, related factors, <strong>and</strong> to characterise<br />

engineering behaviour at deep <strong>and</strong> shallow levels<br />

(Figures 7.2 to 7.18). Wea<strong>the</strong>ring may be related in a general<br />

sense to depth below ground level, but this is not a simple<br />

relationship <strong>of</strong> decreasing wea<strong>the</strong>ring with increasing depth<br />

in <strong>the</strong> case <strong>of</strong> <strong>the</strong> Mercia Mudstone. Moisture content,<br />

density, permeability, <strong>and</strong> strength may also relate to depth.<br />

A large proportion <strong>of</strong> <strong>the</strong> database was assembled from<br />

highway site investigations. Many <strong>of</strong> <strong>the</strong>se have been carried<br />

out on embankments or in cuttings, for example where<br />

existing roads are to be widened. This means that ground<br />

levels reported in <strong>the</strong> site investigation are not necessarily<br />

original natural ground levels. Plots <strong>of</strong> parameters with<br />

depth should <strong>the</strong>refore be treated with some caution as <strong>the</strong>y<br />

contain r<strong>and</strong>om errors, <strong>and</strong> only give a general trend. Depth<br />

relationships shown here should not be used in design calculations.<br />

6.7 BOX PLOTS<br />

The box plot (Figure 6.3) is a simple, compact, graphical<br />

method <strong>of</strong> summarising a frequency distribution based on<br />

<strong>the</strong> robust median <strong>and</strong> quartiles. The alternative term ‘box<br />

<strong>and</strong> whisker’ plot is also in use. The ends <strong>of</strong> <strong>the</strong> box are<br />

drawn at <strong>the</strong> lower <strong>and</strong> upper quartiles (25 <strong>and</strong> 75 percentiles)<br />

with an internal division at <strong>the</strong> median value. Lines or<br />

‘whiskers’ are conventionally drawn from <strong>the</strong>se ends to <strong>the</strong><br />

lowest <strong>and</strong> highest data values that are not ‘outliers’.<br />

Outliers, as described below, are usually represented by<br />

individual crosses beyond <strong>the</strong> whisker ends. Simple<br />

summaries <strong>of</strong> <strong>the</strong> frequency distributions <strong>of</strong> several batches<br />

<strong>of</strong> data may be compared by drawing parallel box plots to a<br />

common data scale.<br />

Figure 6.3 St<strong>and</strong>ard box <strong>and</strong> whisker plot.<br />

32<br />

It is possible to grasp <strong>the</strong> major characteristics <strong>of</strong> a distribution<br />

at a glance by using box plots. The centre <strong>of</strong> <strong>the</strong><br />

distribution is shown by <strong>the</strong> median crossbar within <strong>the</strong><br />

box. An indication <strong>of</strong> spread, <strong>the</strong> interquartile range is<br />

shown by <strong>the</strong> length <strong>of</strong> <strong>the</strong> box. The whiskers illustrate <strong>the</strong><br />

tail lengths <strong>of</strong> <strong>the</strong> distribution. The relative position <strong>of</strong> <strong>the</strong><br />

median crossbar within <strong>the</strong> box <strong>and</strong> <strong>the</strong> relative lengths <strong>of</strong><br />

<strong>the</strong> whiskers indicate <strong>the</strong> skewness <strong>of</strong> <strong>the</strong> distribution.<br />

To a first approximation <strong>the</strong> confidence with which <strong>the</strong><br />

parameters <strong>of</strong> an actual distribution can be used to infer<br />

those <strong>of</strong> <strong>the</strong> total population increases as <strong>the</strong> square root <strong>of</strong><br />

<strong>the</strong> number <strong>of</strong> data values. Thus if <strong>the</strong> width <strong>of</strong> <strong>the</strong> boxes is<br />

drawn in proportion to <strong>the</strong> square root <strong>of</strong> <strong>the</strong> size <strong>of</strong> each<br />

data set, <strong>the</strong> relative significance <strong>of</strong> each can be compared.<br />

The box plot has two particular limitations as a summary<br />

<strong>of</strong> a geotechnical property distribution. There is a simple<br />

convention to determine whe<strong>the</strong>r a value will fall within a<br />

tail whisker or be classed as an outlier. The lower <strong>and</strong><br />

upper cut-<strong>of</strong>fs are 1.5 x IQR below <strong>the</strong> lower <strong>and</strong> above <strong>the</strong><br />

upper quartiles respectively. However, this approach is<br />

ra<strong>the</strong>r too simplistic where <strong>the</strong> distribution is appreciably<br />

non-Gaussian. In <strong>the</strong>se cases reasonable tail values will be<br />

classed as outliers <strong>and</strong> vice versa. It would be preferable to<br />

determine <strong>the</strong> two cut-<strong>of</strong>fs separately, with regard to <strong>the</strong><br />

distribution in each tail area. This would also help in determining<br />

a realistic spread or ‘range’ within which <strong>the</strong> great<br />

bulk <strong>of</strong> <strong>the</strong> data distribution falls.<br />

The second limitation is again concerned with <strong>the</strong> tail<br />

areas. By far <strong>the</strong> greatest distinction between <strong>the</strong> many distributions<br />

encountered is to be found in <strong>the</strong> tail areas. The<br />

central part <strong>of</strong> a distribution is usually very well defined by<br />

just <strong>the</strong> median <strong>and</strong> quartiles. The conventional box plot<br />

gives minimal information beyond <strong>the</strong> quartile box.<br />

6.8 EXTENDED BOX PLOTS<br />

A refinement <strong>of</strong> <strong>the</strong> box plot was devised by Hallam (1990)<br />

to provide a more comprehensive representation <strong>of</strong> <strong>the</strong><br />

frequency distribution <strong>of</strong> geotechnical data sets’ distributions<br />

particularly in <strong>the</strong> tail areas. This is referred to as <strong>the</strong><br />

'extended box plot' (Figure 6.4) <strong>and</strong> is used here to<br />

summarise statistical data for most <strong>of</strong> <strong>the</strong> geotechnical<br />

parameters <strong>of</strong> <strong>the</strong> Mercia Mudstone.<br />

These plots are constructed from <strong>the</strong> 0.5th, 2.5th, 10th,<br />

25th, 50th, 75th, 90th, 97.5th <strong>and</strong> 99.5th percentiles <strong>of</strong> <strong>the</strong><br />

data sets. The selected percentiles have been chosen as a<br />

compromise between practical geotechnics <strong>and</strong> statistical<br />

rigour. For <strong>the</strong> former, <strong>the</strong> simple percentages should be<br />

readily recognisable <strong>and</strong> useful. From <strong>the</strong> point <strong>of</strong> view <strong>of</strong><br />

<strong>the</strong> latter, <strong>the</strong> selection is such that <strong>the</strong> percentages plot at<br />

approximately equal intervals for normally distributed data.<br />

The 25th, 50th <strong>and</strong> 75th percentiles are used to construct<br />

a central box with a median division, as for <strong>the</strong> st<strong>and</strong>ard<br />

box plot. The remaining percentiles are used to define a<br />

series <strong>of</strong> subsidiary boxes to ei<strong>the</strong>r side <strong>of</strong> <strong>the</strong> central box.<br />

In order to distinguish between, <strong>and</strong> readily recognise, <strong>the</strong><br />

successive boxes, <strong>the</strong>y are shaded alternately from <strong>the</strong><br />

centre in complimentary pairs. Thus <strong>the</strong> outer limits <strong>of</strong> <strong>the</strong><br />

shaded boxes will fall at <strong>the</strong> 0.5th, 10th, 90th <strong>and</strong> 99.5th<br />

percentiles.<br />

An indication <strong>of</strong> <strong>the</strong> skewness, <strong>and</strong> even <strong>the</strong> kurtosis, <strong>of</strong><br />

<strong>the</strong> data distributions may be obtained by comparing <strong>the</strong><br />

relative width <strong>of</strong> <strong>the</strong> boxes, as <strong>the</strong>y will be <strong>of</strong> almost equal<br />

width for a normal distribution where <strong>the</strong> data scale is<br />

drawn arithmetically. Logarithmic scaling is used for those<br />

parameters that generally have distributions that are approximately<br />

log-normal. Various measures <strong>of</strong> <strong>the</strong> spread or

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