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Table 5.3: Summary <strong>of</strong> statistical comparison <strong>of</strong> radial and tangential current mmponents<br />

computed h m the simulations. The mean and standard deviations <strong>of</strong> the<br />

three datasets are denoted by - and m, respectiwly, and the standard deviation <strong>of</strong> the<br />

regression <strong>of</strong> y on 2 is la<strong>be</strong>lled 8. Caes (1),(2) and (3) correspond to azimuthal m-<br />

tents <strong>of</strong> 12'. 20' and 36' respect~veiy. TU table summarizes the statistics associated<br />

with the scattergrams <strong>of</strong> Figure 5.6<br />

the variable increases (Montgomery and Peek 1531). An analow here is the differme<br />

in the slope ermr <strong>of</strong> a line estimated from a smd num<strong>be</strong>r <strong>of</strong> 'closely spazed. points<br />

as oppmed to s large num<strong>be</strong>r which are 'widely spaced'. L the ammt we, 92% <strong>of</strong><br />

the <strong>total</strong> variation seen in the tangential components is explained by the regression.<br />

5.3.2 Real Data<br />

Figure 5.7 displays the results <strong>of</strong> the paformanee <strong>of</strong> the algorithm, using real radar<br />

data, in the form <strong>of</strong> scattergr-. The graphs illmtrate that the emr in the tangen-<br />

tial component estimate <strong>may</strong> <strong>be</strong> dependent on the angular extent <strong>of</strong> the sector. This<br />

was also observed in the simulated data examples. However, the variability <strong>of</strong> the<br />

scatter about the unity slope line for the tangential component estimates are quite<br />

different from the simulated examples.

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