Fig. 1.
Fig. 1 shows the occurrence, in per cent, of crimes of both the classes considered for each month of the year, together with the monthly meteorological means, computed from the records for nineteen years. The expectancy curve in the occurrence table is based upon the supposition that the months of the year are all of the same length, and that the numerical expectancy would be one twelfth, or eight and a third per cent for each. It will be seen that the crime curves are for the most part below the expectancy for the winter months, and above it for the summer (except for April, and suicides for June), showing the maximum for the latter class in May and for murders in March. Morselli shows[C] that for most European countries suicides are at the maximum in June, though a considerable number show that condition for the later spring months. A study of the general meteorological means, shown upon the same plate as the occurrence table, fails to indicate any good reason for irregularity of the crime curves. The "month" columns read from the top to the bottom of the chart, and by following that for May, for instance, which month shows the maximum for suicide, we find that the meteorological condition for each class of data is about halfway between the extremes for that class for the year, while for January (minimum suicides) each class is by far more divergent. Yet a mean, like those considered in this table, is but the average of the extremes, and those months which show great per cents of crime also present great extremes of condition, which fact, interpreted in the light of those disclosed by the charts yet to be considered, make the occurrence curve more explicable.
Fig. 2.
Wind.—An explanation of the various curves in Fig. 2 may serve for the series following, so I give it somewhat in detail. The vertical distances from the base line indicate per cents, and the distances from left to right, divided into columns, the maximum velocity of the wind per hour for the days tabulated. In the "normal" curve every day for five years was considered, and it was found that seven per cent of the days for that period showed a maximum velocity of between one and ten miles (first column), forty-eight per cent a maximum velocity of between ten and twenty miles (second column), nineteen per cent a maximum velocity of between twenty and thirty miles, and so on, as indicated by the curve. Now, it can readily be seen that this normal curve may also be considered the expectancy curve—if the wind has no effect. That is, if forty-eight per cent of the days of the year show a maximum velocity of the wind, between ten and twenty miles an hour, the law of probability would give us the same per cent of the crime for the year on such days if this meteorological condition were not effective.
What we do find, however, is indicated by the other curves, and any increase of crime over expectancy may in this case be ascribed to the wind. We notice that for slight velocities (one to twenty miles an hour) the crime curves are below that of expectancy, but we can see that if the sum of all the per cents for any one curve is one hundred, and one is forced above the other at any part, there must be a corresponding deficiency at some other part. So we may, perhaps, with justice suppose that these mild velocities do not exert a positively quieting effect emotionally, but simply a less stimulating effect than the higher ones. For velocities of between twenty and thirty miles a marked effect is noticeable, and under those conditions the proportion of suicides to that expected is 37:29; velocities of from thirty to forty miles, 14:11; of forty to fifty miles, 7:2; of fifty to sixty miles, 0.4:2.6; of fifty to sixty miles, 0.2:2. The curve for murders shows the increase to be slightly less than for suicides, but the same general relation is preserved throughout. The value of such curves is, of course, somewhat proportional to the number of observations made and recorded, and we must confess that two hundred and sixty (suicides) and one hundred and eighty (murders) is a hardly sufficient number from which to deduce a definite law, but we can hardly doubt, even considering this somewhat limited number, that the wind is, in our problem, a factor of no mean importance.
Fig. 3.
Temperature.—Fig. 3 is intended to show, in a similar manner, the relation between expectancy curves, based upon conditions of temperature, and the actual occurrence of the crimes in question. With this class of data, as well as that for the barometric readings and humidity (Figs. 4 and 5), both the maximum and minimum readings are considered. This was done instead of taking the mean of both for the day, since in many cases the latter might be quite normal, while one or possibly both the former might exhibit marked peculiarities. All the curves were constructed precisely as in the chart just considered, and those marked "normal" are again the expectancy curves. An inspection of the chart shows no marked discrepancies till we reach the higher temperatures. For the lower the coincidence for all the maximum and all the minimum curves is not exact, but somewhat similar. When, however, we reach for the minimum curves, temperatures of from 40° to 50° and from 50° to 60°, which means that for the per cent of days indicated, the temperature did not go below those points, the per cent of crime exceeds that expected under the conditions in the proportions of 22:16.5 and 24:18 (suicides), and 21:16.5 and 29:18 (murders).
The same general relation exists between the maximum curves, where it is shown that for temperatures between 80° and 100° the actual crime is about thirty-three per cent in excess of the expected.