Different ways of plotting the data

Next we will show that the basic distance/time data can be manipulated and plotted in different ways. For instance if we now divide the distance by the time for each record, we get the average speed, V, in metres per second. For physiological reasons this is now plotted as a function of time—again on a logarithmic basis—to see how the body produces power (measured by velocity) as a function of time, see figure 3. 

Notice that there is far more structure in the speed/ time graph than its innocuous time/distance equivalent and quite different regimes can now be identified. For instance, we notice that for short distances, the average speed seems to rise from the 50 m event to a maximum at around 150 m and then drop off. The reason for this is quite simple because the runner starts from rest, he/ she needs to accelerate up to maximum speed, then, after a certain time, he/she begins to tire and hence slows down, see figure 4. 

How can this data be best represented and what further information can we extract from it If we now plot the distance/ time data over the range 50 to 400 m on a linear basis—as shown in figure 4— three things are obvious. First, the data we have plotted appears to extrapolate to a non-zero intercept on the time axis when the distance is zero. We can call this time the acceleration time. To, (the more mathematically 

This acceleration time does contain a real time, that is the reaction time from the gun being fired to start the timing to the runner s legs receiving the nerve-impulse message to commence running, i.e. a fraction of a second. 

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