PROVING THINGS 11: LIES, DAMN LIES AND…
There has, over the years, been some considerable controversy about the use of “statistics” in criminal cases. Some civil cases have shown that judges are sceptical of the use of statistics in individual cases, preferring to base decisions on the evidence before them.
EVEN A SECRETARY OF STATE CAN’T RELY ON STATISTICS
This is an issue considered in the judgment of His Honour Judge Lochrane in Ryanair Limited -v- The Secretary of State for the Home Department  EWFC B5.
THE GREEK PASSPORT QUESTION
The question was whether an airline should have noticed that an ostensibly Greek passport was, in fact, forged. The test was whether it was “reasonably apparent” that this was not the genuine article.
Another feature of this case is the evidence produced, largely, I think, on behalf of the Secretary of State, of statistics which it is suggested support the suggestion that the problems, particularly with Greek passports, should have been reasonably apparent to the Appellant’s ground handling staff.
Dr. Staker has with some considerable tenacity and great eloquence attempted to support the statistical evidence produced by the Secretary of State. I made it plain in the course of argument, and I make it plain again now, whilst I am not disputing the possible veracity of the conclusions Dr. Staker seeks to draw from the statistical evidence, it seems to me very clear that the statistical evidence produced does not go anywhere near supporting those conclusions before me.
CONSIDER THE EVIDENCE FIRST AND “PROBABILITIES” LATER: JACOB -v- KINGS COLLEGE
Mr Justice Jay in Jacobs -v- King’s College Hospital NHS Foundation Trust  EWHC 121 (QB)
The central point to be made is that the judge rejected a submission that he should decide the case on the basis of the “inherent probabilities” and that it was improbable that a doctor would have missed the hernia.
I cannot accept Mr Gibson’s suggested approach which is in some way to weigh up and assess the competing inherent probabilities, and to conclude that the combined chance of Mr El-Hasani and Ms Grandy-Smith “missing” (in their different ways) an indirect inguinal hernia must be lower than the chance of recurrence stricto sensu. This approach may well appeal to a mathematician or statistician, and there are occasions where statistics and epidemiology have a role in the judicial decision-making process, but this is not one of them. The difficulty is that there is no comparison of like with like, and no proper basis for placing any sort of figure on the chance of an experienced surgeon making a mistake of the suggested nature. However, that is not to say that the inherent probabilities cannot be viewed more generally and impressionistically, a point to which I will be coming later.
There are no “keys” to the notionally unlocking of this case, in the sense that a judicial decision on any one specific point may be said to determine the outcome. All the evidence has to be weighed in the balance at all material times, with the judicial telescope, or microscope, constantly shifting in its power of magnification, bringing certain facts in and out of view, and then back into focus.
STATISTICS ARE NOT EVIDENCE OF RISK OF COUPLE BREAKING UP IN FATAL ACCIDENT CASES
It is not uncommon to see defendants in fatal accident cases arguing – “well the couple could have divorced in any event.” This issue was considered by Tudor-Evans J in Wheatley -v- Cunningham  PIQR Q100. The claimant’s husband was killed in a car crash. The defendant argued that, despite the evidence that this was a happily married couple, a discount should be given for the “risk” of divorce.
“Mr. Tucker further submitted that there is a special factor which operates as a discount in this case and that is the risk of divorce. It is suggested that this must be reflected in the multiplier. Counsel did not argue that there was the slightest risk of a separation at the time of the death. The evidence is very strongly to the contrary. He based his submission upon statistics which Dr. Pfeffer accepted in cross-examination are accurate and which show that currently 40 per cent. of marriages in this country end in divorce…
As to the risk of the breakdown of the marriage, I have to evaluate all future chances (save the chances of future children). In Davies v. Taylor  A.C. 207, the plaintiff widow had deserted the husband before he died and she resisted all his offers to return. He had started divorce proceedings. In proceedings under the Fatal Accidents Act, the plaintiff claimed a dependency on the deceased. The claim failed. Lord Reid at page 212 of the report said:
“He wanted her to come back but she was unwilling to come. But she says that there was a prospect or chance or probability that she might have returned to him later and it is only in that event that she would have benefited from his survival. To my mind the issue and the sole issue is whether that chance or probability was substantial. If it was it must be evaluated. If it was a mere possibility it must be ignored. Many different words could be and have been used to indicate the dividing line. I can think of none better than ‘substantial’ on the one hand, or ‘speculative’ on the other. It must be left to the good sense of the tribunal to decide on broad lines, without regard to legal niceties, but on a consideration of all the facts in proper perspective.”
Applying this text and bearing in mind the evidence that the plaintiff and her husband were very happy together, I refuse to take mere statistics into account and so reduce the multiplier. It is pure speculation whether this marriage would have fallen into the 40 per cent., assuming that these statistics will prevail in the future.”
There a interesting academic article on this issue:
- Proving things 1: Civil Evidence Act notices will not cut it
- Proving things 2: evidence to support a claim for damages must be pitch perfect.
- Proving things 3: the complete absence of evidence means the court will not speculate
- Proving things 4: Witnesses who just aren’t there.
- Proving things 5: witness statements and failing on causation.
- Proving things 6: “That’s what I always do” & proving causation.
- Proving things 7: If you don’t prove a loss you don’t get an order.
- Proving things 8: a defendant must prove that a failure to wear a seatbelt made a difference.
- Proving things 9: the role of experts
- Proving things 10: “He said, she said”: the difficulties of recollection.