All these comments about statistics don't seem to even begin to understand statistics.
1) Yes, we can use the chi-squared test here - the small number of events is built into the p value.
2) No, we do not need to include all murders, as we are not testing for murders. We are testing for mass shootings. This line of reasoning is the same as saying we cannot test for rotten apples only, we can only test if all fruit is rotten. Statistics on categories is acceptable and meaningful if apples are a specific kind of fruit, or mass shootings are a specific kind of crime. We can't draw an conclusion about crime, but we can draw a conclusion about mass shootings.
3) These statistics prove only a single thing: mass shootings in USA are likely random events and have a mean value of ~2.
The following conclusions are applicable:
- Mass shootings are likely not a 'copycat' crime,
and each event is likely completely independent
of any other event occurring.
- You should expect about 10 mass shootings over the
next 5 years. Not so nice...
Following conclusions are NOT applicable:
- Gun laws have any effect. Gun laws may or may not
decrease the average, these statistics do not say.
- No measures that have been put in place to reduce
mass shootings (I assume there are?) have had any
effect so far. They may have had a positive or
negative effect, but these effects may be small
or may be cancelled out by other, opposite effects.
- The chance of a mass shooting is stable, and no
increase or decrease in events seems to be happening.
The distribution fit test only shows us on the
aggregate data, and that it does fit that distribution.
The correct way to check for this is to break the data
set in half, and compare the first set against the
second set.
And now we return you to our regular statistics hate...
EDIT: Or not - nobody is questioning the real possible problem here: the data itself?
This seems to imply there are FAR more mass shootings per year than indicated by the data. None of my conclusions above are correct if the data itself is wrong, and I don't even live in the USA so I can't vouch for the correctness of the data.
Your point 3 is incorrect. The analysis fails to show that the data observed can be distinguished from data drawn randomly from a Poisson distribution of mean 2.
The double negative here and concept of "distinguishing from" is important. In particular, this result does not rule out being underpowered by which we'd mean to say that given infinite tragic observations we may be able to make a case to distinguish the data from the random distribution, but since we only had a little that effect was buried.
Again, you cannot even say things like "are likely not" and "should expect" because those are epistemologically reversed from what we can state. What we can say, in parallel, is
- We do not have evidence here suggesting that mass shootings are copycat crimes (if we buy that copycat crimes would lead to non-Poisson distribution of mass shootings).
- We have not been able to show it flawed to predict 10 mass shootings over the next 5 years.
It's definitely a pain in the ass to rework all your statements this way, but it's also necessary for them to mean anything resembling truth. Statistics is a fickle beast, especially frequentist methods interpreted predictively. This song and dance, however, is required to make the general process of using statistical tests trustworthy enough over time.
I blame Christmas and lack of sleep - I misread the actual article. Article is completely wrong.
" ... found a p-value of 0.18. What does this mean? It suggests that there is no evidence of clustering beyond what you would expect from a random process ... "
Above is incorrect. What the author is actually testing is the following statement:
The mass shooting data points come from a Poisson
distribution with an average value of 2
However, the test he is using can only prove this statement to be false: it CANNOT prove that the statement is true. So the only thing the author proved is that the statement may or may not be true. (For more, read up on a null hypotheses, the scientific term for this.)
All the author has proven is that there is an 18% chance that the data does not come from a Poisson distribution. ~1 in 5 chance of being wrong is not something you assume to be right. Author needs to learn statistics.
All the author has proven is that there is an 18% chance that the data does not come from a Poisson distribution.
This isn't right either. You've committed the inverse fallacy [1].
The correct way to read that p-value is: "If the data came from a Poisson(2) process, it would be 18% likely to have deviations at least as different from poisson(2) as the observed data."
The test gives no insight into the probability that the true distribution is Poisson or Poisson(2).
All any statistical twst can do is give you a probability. Nothing can be "proven". In any event, the possibilities are not "random" and "not random", e.g. We could be seeing a poisson distribution with a very small copycat effect.
What is pretty clear is that the US has an obscenely high rate of gun violence, which is what we ahould be debating. Several thousand children die each year, and nearly one and a half Sandy Hook's occur each day.
The Brady list includes many incidents of types excluded by the OP's data source, including gang-related violence, incidents that occurred in non-public locations such as private residences, and cases where fewer people were killed.
The Brady data is flawed because they count folks who likely could shoot each other (e.g. two gangs). Also, it is best to get data from advocates verified by independent sources. I tend to use the CDC or someone who explains clearly their methodology.
>These statistics prove only a single thing: mass shootings in USA are likely random events and have a mean value of ~2.
The whole "it is random" BS is based on the pre-assigned value of 2 per year. Why pre-suppose that 2 per year is an acceptable norm, that is not problematic in itself?
Consider a US with a mean value of 10,000 mass shootings per year, with the occasional 0, 20.000 or 50,000 etc mass shootings fitting the poisson distribution. Using the same methodology as the article, the same "conclusion" would have been reached, that mass shootings are random.
This is a major misunderstanding at what "random" implies in this context. It just means that the motives and decisions at the individual level to "go for it" are triggered independently and with the specific year bearing no influence. That is, it proves that the specific events are not co-ordinated.
This is mighty fine, but it doesn't at all mean that the cultural / law / etc climate that makes even considering an attempt at one of these events possible (much more for a median of 2 a year) is "random" or non changeable by human intervention.
Way to misapply statistics. As they say, there are lies, damned lies, and statistics.
As an extreme example, in a country where there are no guns (either legal or illegal), there would be no mass shootings AT ALL. No "spontaneous random activity" pertaining to mass shootings could change that.
In a similar, but more practical way, if other western countries have a median of about 0 mass shootings per year for decades (with the occasional exception), this tells us that even if the number of mass shootings per year in the US is random, the fact that it has mass shooting at all is not random but a cultural/structural result.
Why pre-suppose that 2 per year is an acceptable norm, that is not problematic in itself?
No one does. The rest of your comment is a riff on that point, so I won't respond to that. This (brief) analysis was trying to answer the question: are there more mass shootings now than in the past? The answer was no, and that there are about 2 a year.
This point is entirely independent from the question, what can we do to decrease the number of mass shootings?
>The whole "it is random" BS is based on the pre-assigned value of 2 per year. Why pre-suppose that 2 per year is an acceptable norm, that is not problematic in itself?
There is no such presupposition. The way that you estimate the mean parameter in a Poisson distribution is by taking the average over your sample. "2 per year" is not a normative statement; it's an observation of history.
In statistics, you don't get to make a moral judgment when estimating parameters. If you do that, you will get the Wrong Answer.
A minor point here, but relevant since the OP is emphasizing the importance of understanding the Poisson distribution - if the mean really was 10,000, any observation outside the range [9,500, 10,500] would be extremely unlikely.
Apples is a clear easily distinguished subset of fruits wish is useful to predict its taste, expiration date, gastric tolerance, etc.
There is many widely different definitions of what a mass-shooting is (about apples we don't); the article is using a definition from the motherjones website; their definition is strict but randomly chosen; like somebody claiming that only red apples are real apples and the other ones are not; with no data to support that this definition creates any useful subset that can or should be statistically analysed; the statistical sample is already biased by absolutist and arbitrary boolean conditionals which render null any conclusion extracted from its statistical analysis (e.g shooter killed 3 people instead of 4 and therefore is not a mass-shooter)
I actually found the author's comparison to a poisson distribution with a mean of 2 a bit disturbing.
Why should americans expect an average of 2 mass shootings a year? What the heck is wrong with that country that you can expect TWO mass murderings a year?
If you compare the statistics to a poisson distribution with a mean of say, 0 (you know, like most countries, you don't expect ANY mass shootings in a year AT ALL), then you cannot claim randomness any more.
The premise is what bugged me the most - that a mean of 2 is acceptable
You seem to be confused. There's no claim that a mean of 2 is acceptable or anything like that. The fact is that in the last 31 years, we've had 62 mass shootings, and that comes out to an average of 2 per year. You don't get to compare to a Poisson distribution with a mean of zero because you have to use the actual mean, which is 2.
This analysis has nothing to do with whether or not there are too many shootings. It's about whether the shootings occur at a fixed rate, and are independent of each other.
You have it correct in your last sentence although your previous sentence had it quite wrong.
You are correct that the analysis is about whether the shootings occur at a fixed rate. The author had set the expected value of 2 at a given time period, which is to say the author assumes that the 'natural rate' of a mass shooting murder is 2 a year.
The mean across the years has got nothing to do with this IMO. It may have been a good rule of thumb to compare against, but it's not a good one to do an analysis upon. It leads to all sorts of mistaken conclusions, like the one the author made.
You're all partialy wrong. The author wants to test if there is an incrase of mass murders, so he wants to test if the large number of mass murders that occured in 2012 is likely to be due by chance or not. he wants to know if 2012 is an exceptional year or not regarding the average. We dont care what the average is, we want to know if this observed number of mass murder is not likely to be observed regarding the average. His pvalue is small but not small enough to conclude that the distribution of observed mass murders does not fit the model.
No, there's no assumption of "natural rate" or anything like that. The ordinary way of estimating the mean parameter for a Poisson distribution is by taking average value over the sample period (http://en.wikipedia.org/wiki/Poisson_distribution#Maximum_li...).
>The mean across the years has got nothing to do with this IMO.
Well, that's all well and good, but your opinion is irrelevant. This is simply how this statistical tool is used. And crucially, the data fits this model, so objecting to its completely standard parameters is very silly.
take a step back and consider: size of population and history.
Norway has had 0 mass murders since ww2. Yet 18 months ago Norway faced one of the worst mass murdrs in peacetime. Maybe the percentage of people wanting to do such stupid things are the same in Norway as in US, only the population is so small it takes years between everytime there is someone with high enough iq to plan this kind of cruelty and low enough respect of life to actually do it.
Also take a look at Japan. Few shootings but at least during the nineties a couple of attempted mass murders using poisenous gas.
An awful lot of those weapons are provided to those places by outside interests for proxy wars and similar circumstances, at east for more advanced types of weapons. Yes, you can improvise killing tools from a great many things, but the more effective methods tend to be at least somewhat advanced.
Except those areas are also fairly well armed with guns. It just turns out IEDs and suicide bombers are more effective in kill rate than guns in certain situations.
It's worth noting that the population of Norway is tiny, around 5 million, while the USA has ~310m. At 2 shootings a year for 310m Americans, that suggests something like 1 shooting per 155m; 155m is 31x Norway's 5m, suggesting 1 shooting every >30 years.
Assume a lower base rate, and you make just 1 mass murder in the 67 years since WWII a fairly plausible outcome. I'd note that before Breivik, the previous record-setting mass murder was a South Korean policeman, also a small country not known for violence or crime.
This seems like trying to use a hammer (statistics) because you have a hammer, not because it's the right tool for the job.
Essentially, if you look at the incidents, you see enough common factors (increasingly, using semiautomatic carbines, carrying multiple weapons, attacking schools, wearing armor or load bearing gear, etc.) to think there is some common factor at work. The population of random people on the street doesn't pick the AR-15 to do anything, and certainly doesn't pick a school as a target for anything. The solution space here isn't "spree shootings at schools through time", it is traits of spree shootings themselves -- location, methods, etc. They're pretty tightly clustered.
Either there is a common hidden factor, or these incidents are feeding on each other.
I personally don't think gun control is the major tool to deal with this, and don't think violent video games are the problem, but rather the non-stop multi-day press coverage by the media of each of these incidents.
Some insignificant douchebags from a Colorado school became about as famous as the 9/11 terrorists (and far more than fortune 50 CEOs or scientists or classical musicians) by murdering their classmates.
(Columbine essentially as as big a deal for the 'how to respond to shootings' world as 9/11 was to aviation security; previously, you cordoned off the area and called in SWAT to negotiate, thinking it was a hostage situation -- now, the first 1-2 responders on scene move directly to the threat with whatever weapons they have on them at the time, ignore any wounded victims, close, and engage/destroy -- similarly, hijacked airliners are now viewed as air to ground missiles vs. hostage negotiations.)
Every time the media talks about the shooters in one of these situations, making them famous, it reinforces the rational (if defective) choice of someone who wants to be famous at the cost of doing evil to copycat.
The mythological/historical example is Herostratus, who burned the temple of artemis just to be famous.
I don't buy this explanation over the alternatives. It's logically sound but is based on the assumption that spree shooters do so in large part to gain infamy and notoriety.
Given what we know of spree shooters around the world and in the US, they strike me as predominantly desperate, mentally ill people. We had the Columbine shooters who seemed to be more vengeful than fame-seeking. We had the Aurora shooter who didn't do any grandstanding when apprehended, or in fact talk to the media at all. And of course, we had the Newtown shooter who didn't leave behind any notes, manifestos, or in fact any evidence that he wanted to be infamous (even if posthumously).
These don't strike me as people who are driven by the ensuing media coverage.
Don't get me wrong - I've been appalled by the news media surrounding the Newtown shooting, particularly CNN's journalistically abhorrent fingering of an innocent individual, but I don't think the coverage is really the crux of it, and I don't think taking it away will stop them.
I don't think they're doing it consciously to become famous, but out of feelings of inadequacy/lack of agency/bitterness/etc., which subconsciously turns into fame-seeking to try to resolve that. But I have no deep psychological insights here; I've thought about the tactical and trauma care side, but treating the incidents as random events works perfectly well for that.
However, pro for your argument, there is some reporting bias -- we hear about school shootings for days, but we rarely hear about suicides, or murder/suicides, which are far more common; even things like the Sikh temple murders went out of the news in a day or two. Schools are just particularly likely to get coverage and stay in the news.
But if ending the media deification of spree killers converts some of them back into simple suicides, that's a win, really. On the other hand, it seems to have channeled them into a local maximum of "pretend like you're playing Call of Duty, without any real skill or training" -- I'd be a lot more afraid of a halfway competent chemist with no tactical experience deciding to go the full McVeigh, vs. trying to play soldier. I'm personally pretty comfortable with a rifle, but if my goal were mass casualties, it'd be bombs or other technology based attacks for sure.
> And of course, we had the Newtown shooter who didn't leave behind any notes, manifestos, or in fact any evidence that he wanted to be infamous (even if posthumously).
He left plenty of evidence that pretty much guaranteed he'd be infamous. Nothing will do that like several dozen dead bodies. Notes and manifestos are optional.
These assholes may have many different drives but the one thing they seem to have in common is that they pick their targets to guarantee that they will become notorious. Stomping on an ant hill will kill many more but won't put you on CNN.
Apropos CNN, the one thing the media could do with cases like these is to restrain themselves in the way they cover these incidents. I'm pretty sure there is a large element of copy-cat behaviour in here that could potentially be reduced by the amount of media coverage given.
Let me try again: if he had stomped on an anthill to vent his anger you wouldn't have heard about it.
The media decide who gets to be (in)famous and by behaving in a certain way you can get your 15 minutes. Behaving in this particular way pretty much guarantees that. The link between gore and media coverage is firmly established by now so even if in the first few cases you could have said 'that's circular reasoning' after several such cycles you can no longer tell cause from effect.
Hence copycat crimes and other stupidities.
All it took for dumb, angry children to be set on this path was the attention given to the Columbine shooters. Quite a few of these idiots - if not all of them - think those guys were heroes and perceive the media attention given to them (movies, incessant press coverage) as positive.
They want that for themselves to compensate for some perceived inferiority or other shortcoming and so they go the same route.
I think today it is safe to assume that a hunger for fame is at least a component in these shootings.
I can easily imagine that "hunger for fame" is a component in these shootings, but that's not the same thing as "I have evidence to support" or even "is likely."
> He left plenty of evidence that pretty much guaranteed he'd be infamous.
You seem to be confusing cause and effect.
He more likely chose his target because his mother worked there. Even if every shooter is choosing randomly we will only talk about the "media seeking" ones the news covers.
He shot a few more people than just his mother. He could have done that at home. All of these shooters have chosen a target they had some relation to, either they went to the school or they had some other prior history with it.
Still, the decision to attack the school, it's students and not simply one individual is why we are hearing about these.
It's not necessarily to gain notoriety. But there is such a thing as copycat. So reporting about people committing shootings is more likely to cause more shootings. I remember an episode of Newswipe, where a psychologist urged media to:
a) keep the news of violence to local community only
b) do not glorify the attacker by negatively praising him (like a ninja, moved quickly...) or showing him in positions of power (brandishing guns or wearing clothes that hide his face)
c) telling how many people he killed.
Each time one of those news is broadcast, he added, they see a spike in violence. And it seems consistent with how humans regularly behave.
As for other evidence, you'd need to look at crimes and if there is a large number of similar attempts of violence (not necessarily school, but overall mass shootings), grouped around highly prominent cases covered by media. That kind of research and evidence is sadly outside my scope. I'm not sure where you'd find sources, nor how to process them statistically correct.
>Given what we know of spree shooters around the world and in the US, they strike me as predominantly desperate, mentally ill people.
No, we mostly know them in the US, by an order of magnitude more than other western countries. The same with serial killers: the US is up there with some third world nations for more prolific killers, and unsurpassed for total serial killer count, so much that Wikipedia devotes its own page to US serial killers which is larger than the sum page for the rest of the world.
And, desperate, mentally ill people? Could also be the products of a desperate, mentally ill society.
> So much that Wikipedia devotes its own page to US serial killers.
Aside from any of this Wikipedia devotes a lot of pages to US-specific things because it has a lot of contributors in the US. You shouldn't draw any other conclusion from it than that. You'll see a lot of US-bias and US-specific coverage on any topic on the English Wikipedia.
Hello? Someone was claiming the same about other Western countries, so I compiled these lists of mass shooting events in Western Europe in just this century:
From Wikipedia, school shootings in Europe in this century, last two numbers are killed and wounded:
I'm confident that the US cannot hold a candle to Germany, Russia, Cambodia, Bosnia, etc., when it comes to prolific murdering. If you only want to consider individual / non-cooperating killers, they exist in similar proportion across most societies.
Another option is that they are the products of a dysfunctional medical system. In particular, a pretty common recurring feature is that the shooters turn out to have been on antidepressants which are known to cause aggression and/or suicidal tendencies.
Sensationalist media shares culpability by giving this kind of behaviour a strong presence in the public collective consciousness. Being talked about is a powerful reinforcement signal, we are programmed to seek positive reinforcement from the groups with which we identify and negative from 'the enemy.' With the increasing alienation of modern life, it is not difficult to see how this can lead to senseless violence in extreme cases.
The whole thing is a vicious circle, this kind of news has to be sensationalised because we have been steadily desensitised by the media.
As a teenager in the 90s, I remember getting mildly claustrophobic at the thought of watching another Movie or TV Show about a hijacked plane or hostage situation. There were just so many building up to 9/11. Essentially, the messages were things like 'Enemies of America hijack planes', 'Radical citizens plant bombs', and now 'Angry employees/students show up with automatic weapons and body armour.' These are as much statements as they are calls to action.
Let's take a look at this year's Emmy nominations for the best actor category, these actors play: a ruthless corrupt bootlegging politician-gangster, a high school chemistry teacher turned murdering drug kingpin, a vigilante serial killer working in law enforcement, a terrorist war-hero congressman secretly radicalised in captivity and an alcoholic misogynistic deserter ad executive with a stolen identity. The only leading character that does not belong in prison is from a British production. Perhaps this category should be renamed the 'Best Magnificent Bastard' award.
America has this fascination with revealing its weaknesses to 'enemies - both foreign and domestic' and celebrating monsters. Most people learn early on that, unless one is trying to play and remain the victim, painful memories and weaknesses should not be put on public display for the casual friend, enemy and stranger.
When the Newtown shooting made the news, I had the following thought: just 24 hours earlier, there was news of an execution-style shooting near Times Square. Even though the Times Square crime is less horrifying (fewer people, no children, etc.), I would say that it is more relevant for gun policy. Why? Only seven massacres in 2012, but tens of thousands of gang-related shootings.
We have a problem with guns and crime, not with massacres. Massacres happen, and if there were no other murders to worry about I would say we should focus on massacres. The trend in gang violence is very clear: concealable weapons (handguns) purchased on the black market. If you want a sensible gun policy, you need to focus on handguns; gangs rarely use rifles because rifles are too difficult to conceal.
May I ask how gun control is not a tool to deal with that? In other words, what are the differences between Americans and Europeans that prevent most of such violence happening in Europe (mostly at least), other than hard access to guns?
One key fact to observe is that crime without guns in the US is also very high. The US has a stabbing+bludgeoning+poison+etc murder rate of 1.8/100k, which is still higher than murder by all methods in most of Europe. I.e., Americans just like to kill people.
One possible cause is demographics - more than half of our murders are committed by a demographic group making up only 10% of our population, and this subgroup is very uncommon in Europe.
Possibly also the drug war, which is quite connected with violence, race, racism, poverty, urban/suburban/rural migration patterns, public health, human nature, geography, immigration, expansion federal power, military conquest, etc.
It may be a tool, I just don't think it's a major or the main tool, for three reasons.
1) There are enough guns out there now that a ban on new production would have only a minimal effect, a ban on transfers would have only somewhat more effect, and a ban on possession, given that criminals are willing to break laws, wouldn't have a huge effect.
For spree shooters, even a pump-action shotgun or lever carbine and a 10-rd handgun or two (or even just a couple revolvers with speedloaders) would be pretty adequate to kill 50+ unarmed people, even if they weren't 6 year old children. So you'd need to address not just "assault rifles and 100 round drums" but basically most firearms (maybe leave single-shot shotguns/rifles).
2) The cost of ending the media deification of spree killers is almost zero. The cost (in terms of implementation cost as well as loss of rights) of any gun control is far higher. The cost of a comprehensive gun ban and confiscation could be up to (probably localized) civil war. Pick the tool which has the least costs first, especially if it's probably more effective.
3) Even if there were zero guns, you'd have other instruments of death, assuming people had the desire. I'll accept that guns are easier for some of the more amateurish and unmotivated killers (including maybe the CT guy), but Columbine involved bombs, McVeigh was a bomb, and now that the "spree kill and become famous" thing is out there, all it would take would be another McVeigh or two to show how its done and then people would be doing bombings, or running over a bunch of kids at bus stops, or whatever.
In places where drugs and alcohol are banned, they make alcohol out of prunes, get high off glue, etc. It's a lot better to focus on demand than supply.
I think Europe generally doesn't have incidents like this, not because it's disarmed, but because even "losers" in Europe can live a somewhat comfortable life compared to losers in the US. Better healthcare, better social support, etc. Europe has certainly had some serious violence in the past, generally by organized groups that feel they are "losers" vs. individuals, more so than the US. European society seems to have less inequality and thus fewer positive and negative outliers than the US. (Similarly, there is a gender difference in distributions of most traits; men tend toward the extremes; which may be why most criminals and other horrible people seem to be male)
> a ban on possession, given that criminals are willing to break laws, wouldn't have a huge effect
A recurring element in a lot of these shootings is that the shooter gets/steals his weaponry from an uncle, dad's rifle cabinet, a friend or so on. These are the kind of people that would dutifully get rid of their guns if they were banned. Thus closing up a potential source of destructive firepower for nutcases.
> I think Europe generally doesn't have incidents like this, not because it's disarmed, but because even "losers" in Europe can live a somewhat comfortable life compared to losers in the US.
Is there any indication that any of the recent shootings happened because the shooter didn't have any food to eat, no shelter or bad healthcare? Because that's the sort of comfort that a welfare state provides and I don't see the link.
Especially true for minors. True for a possession ban. Less so for sale prohibition or transfer prohibition. More so for sale/transfer prohibition with generous buybacks. (if new-sale is prohibited, prices will rise, so they'll be secured better; if transfer-ban, you'd probably see prices fall (since there's no market), so less of a reason to secure them, ironically).
> [food, shelter]
Clearly they have insufficient mental health services (in the CT case, some of the problem was that he wasn't a minor, and his mother was trying to have him committed). Not so much "how to pay for mental health" vs. general delivery issues.
They do seem to generally be middle class and not starving or anything, but I meant "failure" in the sense of social standing/competitiveness/etc., not just absolute poverty. After all, even a fairly poor person today lives (in absolute terms throughout history) fairly comfortably, but feels the relative social standing and status.
So if you're sincerely asking what differences other than gun ownership might be preventing violence, that'd be a good place to look. Time Magazine just had a good piece on the cultural differences that lead to a safe gun culture there: http://world.time.com/2012/12/20/the-swiss-difference-a-gun-...
Switzerland is very special for multiple reasons. They have a direct democracy, federal system with very small cantons (equivalent of states) and until very recently every mail had an assault rifle at home. They're also very law-abiding citizens in general with >80% of crimes being commited by immigrants. I like swiss model a lot, but it's not 100% clear it can be scaled to a bigger country or if you need centuries of public awarness (they never had a king for example). The differences are so big, it's really really hard to compare with any other country.
All true and I admire Switzerland for all those reasons. However, at least some aspects of the "Swiss gun culture" actually exists in the U.S., among enthusiasts, who have a serious "culture of responsibility and safety" and teach their kids the same. Go to, say, a competitive shooting event, and you'll get an entirely different impression of gun owners than you may have now. As someone in the Time article says, "If people have a responsible, disciplined and organized introduction into an activity like shooting, there will be less risk of gun violence."
For the patriotic side, check out Project Appleseed (http://www.appleseedinfo.org/), which conducts weekend courses on rifle marksmanship and Revolutionary War history. (It's run by volunteers, and costs $70 for a weekend.)
This culture used to be more widespread in the U.S., back when rifle shooting was a high school sport. The more we crack down on legal gun ownership, the more we stamp it out.
Violent offenders were the [victims]
of most State prison homicides
(61%), and their jail homicide rate
(5 per 100,000) was over twice that
of nonviolent offenders (2 per
100,000).
== Interesting to note that Prision murder rates are higher than many states in the US, and many countries in europe. None of this is guns, though. It seems in the abscence of weapon x a killer will use y or z. lots of people killed this way with pens and spoons etc.
A part of this is Europe's abhorrence of violence in general dating back to the end of world war II. Those lessons are slowly being forgotten but there definitely still is a strong undercurrent to that effect.
Having a half decent welfare program is another element in there. But with the current crisis and the upcoming pension plan troubles it remains to be seen if we can sustain that and if we can not I predict an increase in crime and associated violence.
It's not a great choice for home defense, however - it's actually quite bad at killing people. A nutjob with a couple of 5.56mm holes can still stab you a bunch of times before he bleeds out.
A shotgun is a far better choice.
Fun fact: the reason the military went with 5.56mm is that killing power is less important for the military (wounding a guy takes him out of the fight, as well as 1-2 of his buddies to take him home), while ammunition weight is a big deal (lighter ammo = less for a soldier to carry).
Just to bring this to something technical and marginally less depressing than discussing mass murders on HN on Christmas, 5.56mm got a lot better with the 75gr TAP and 77gr Sierra OTM/mk 262 vs. M193 or M855 ball. My HD long guns are a tricked-out Mossberg 590A1 and an M1A 16" .308 carbine with 180gr ammo, though.
I mean, the military even manages to make 9mm ineffective. LC 115gr 9mm FMJ is maybe 10% as effective as my Speer Gold Dot 124gr +P JHP.
SWAT entry teams use them. At close range they're quite a bit more effective than at the longer ranges often encountered in military situations, since the bullet is likely to fragment.
At the same time, tests have shown less overpenetration after encountering drywall than hollowpoint handgun rounds, which tend to fill up the hollowpoint without expanding and then go through several barriers.
This is all well and good, but what you say does not invalidate the use of statistics. That is to say, even if there are, as you claim, common factors between the events, they may still be randomly distributed in time.
So your hypothesis is that considering only school shootings, you can prove that they are not random events lets say at 95%. Care to make the case using science rather then just waving your hands?
My argument is that something other than time distribution is a much better way to see that they're connected. They may be randomly distributed through time, or not, but they're clearly not randomly selected from the set of all possible mayhem activities.
Mass shootings are rare enough that you're going to get poor stats due to granularity. It might be more interesting to look at stats like homicide rate.
The U.S. has a homicide rate that is second only to Russia in the G8, and is more than 3 times higher that of any G8 nation besides Russia. This sets off warning bells for me...
Normally I'd love to dig a little deeper, but it's time for me to play Santa. Merry Christmas!
Yes, let's exclude statistics in order to normalise them. Because if we cut out the bits of statistics that sway them, we can claim the distribution is the same as elsewhere!
By grouping statistics into these things we call "countries" we are also "excluding" certain statistics. For instance, why are we ignoring cartel murders just south of the US/Mexican border even though the US drug market is the driving factor?
The parent comment is providing a better, more specific grouping that helps shed light on where murders are actually happening in the US and points us towards where we need to focus our efforts if we want to actually change the murder rate in the US. Inner city interventions will result in the greatest improvements to the murder rate, whereas focusing efforts elsewhere has literally zero chance of bringing the murder rate into line with the rest of the G8 because that's not where the murders are happening.
The parent comment is introducing a new variable which may or may not be useful in, as you suggest, providing targeted approaches to reducing deaths by firearms.
It still flies in te face of convention which still treats a whole country as a whole country, in the perhaps naive assumption that by averaging the nations stats you will be able to get a good comparison of what the average citizen puts up with an thus providing a ground for comparison with other average citizens in other nation-states, regardless of their level of development, or even, indeed, if they have 'inner city slums'.
And all that is leaving aside the matter of whether the statement is actually true, as questioned by a number of other threads
It's not a new variable, it's just a new, equally arbitrary, line on the maps.
In slums you have a completely different expectation of law enforcement and law enforcement presence, social service, education, economy, transportation, etc. In every respect except for lines on a map, slums are a completely different world. "Countries" are an obscenely coarse classification, we should always be open to more fine-grained analysis.
What a great comment. Encouraging people to look beyond their backyard to see the effects of what they do day to day is not easy, but it is important. Looking at stats for murder, poverty etc is more meaningful when examined globally.
What the heck is wrong with Northern Idaho? Elko Nevada? So Cal's inland empire? I didn't think there was anyone to kill in western New Mexico. The Mississippi Delta also doesn't look like a healthy place to live.
If we excluded Louisiana, the murder rate would probably plummet to mostly normal levels. And it just isn't New Orleans.
I don't know if the person you're responding to is actually correct or not, but the map you're referring to is very misleading. The places you named--and, not coincidentally, many of the places on the map with the highest murder rate as a percentage of population--are all sparsely populated.
Notice that the many of the places with the lowest murder rates also tend to be sparsely populated. What you're seeing is the increased variance that one should expect to see when dealing with smaller sample sizes, not evidence that small towns are more dangerous than big cities.
I bet we would see more geographic correlation with not too much variation in city areas (e.g., the Delta is still a dangerous place to live, which would correspond to anecdotal evidence). Unfortunately, I can't google up a decent gun homicide heat map.
Elko, Nevada is a mining town; having grown up in one that was such until a bit after WWII I can tell you these have long lasting cultural differences that include higher crime rates.
Nope. It is both. From dictionary.com "ton" entry:
"7. Informal a. A large extent, amount, or number. Often used in the plural: has a ton of work; gets tons of fan mail."
Also, please provide a reference.
Since you asked politely, here's one. Manhattan, which I don't consider an "inner city slum" had 88 homicides in 2005, 102 in 2006, 68 in 2007, 62 in 2008, etc.
That's comparable to Ireland, Switcherland, Denmark, Austria, countries of 3 to 6 times the population of Manhattan (1.6), and 3 to 4 times the percentage of murders in Germany (adjusted for the 80 million population).
You just compared full countries to a densely populated city which is surrounded by Burroughs with notorious ghettos (in parts of the Bronx, Harlem, Brooklyn, Queens and in New Jersey).
Not only that, but Manhattan is the entertainment center for the surrounding Burroughs and cities, where a lot of violence happens.
This is true in Toronto as well, our "club district" has one of the highest murder rates from people visiting who don't live in the club district.
I don't think Manhattan makes a fair comparison and doesn't disprove the OP's comment.
For anyone who's interested, this blog post piqued a very morbid interest in me, and so I decided to have a look at the data.
Here's a distribution of the number of days before the previous incidents (as reported by MotherJones. I'm personally not familiar with the number of shootings in the US, which according to different sources ranges from very few to way too many): http://imgur.com/Onoxv . The colours represent the group of how many incidents happened in the 180 days prior to the incident.
Here is the distribution of the number of incidents 180 days prior to an incident: http://imgur.com/9VTjQ
There is absolutely an observed trend of copycat school shootings which flies in the face of randomness.
That said, I think this trend is hidden from this dataset because it relates specifically to mass shootings, including only those incidents in which the shooter took the lives of at least four people.
I would hypothesize that each major shooting is followed in the succeeding months by a number of slapdash copycat shootings, in many of which less than four people are killed by the shooter.
Since mass shootings are such a rare events, the data is overdispersed, so a negative binomial distribution is likely more appropriate than a Poisson distribution. This, along with quasi poisson, is commonly used by criminologists to account for such problems.
Deviations from the Poisson distribution are exactly what he is testing for. The paper you referenced discusses how to model in the presence of overdispersion. Not how to test that as a hypothesis.
Moreover Poisson distributions are generated from events that occur in a very small fraction of all opportunities, but with many opportunities each time period. So, unless the timing of shootings is correlated (again, the thing he is testing for), this is a perfect use case for the Poisson distribution.
This was a great article, but I'm not convinced mass shootings are completely independent. Given the media attention, it is very likely that event n+1 was, in some way, impacted by event n.
I don't have any evidence to back this up, so I could be (and I hope I am) completely wrong. But if I'm right, then I think it would imply we need to reduce the correlation between events. And it is likely the media that provides that correlation. Instead of reporting about the <insert your word here> that causes these events, report on the impacts of these events. It would, hopefully, stop deifying the perpetrator, which might reduce the likelihood of other perpetrators from doing the same.
There should be some way to formalize this into a hypothesis. Testable with the same data I mean. If you were correct we should see more clustering then we do with a random sample.
You'd get weird mixture model type systems. There are certain subclasses: school-based vs non-school-based. You'd have to control for this since school-based shootings are highly temporally correlated. But then maybe there's crossover too. Like everything, estimating these things with more complex models is hard to do right, and findings are usually overstated.
Edit: it is unclear at this stage if this event would qualify for inclusion in the numbers according to the criteria in the article. Below are the used criteria.
The killings were carried out by a lone shooter. (Except in the case of the Columbine massacre and the Westside Middle School killings, both of which involved two shooters.)
The shootings happened during a single incident and in a public place. (Public, except in the case of a party in Crandon, Wisconsin, and another in Seattle.) Crimes primarily related to armed robbery or gang activity are not included.
The shooter took the lives of at least four people. An FBI crime classification report identifies an individual as a mass murderer—as opposed to a spree killer or a serial killer—if he kills four or more people in a single incident (not including himself), and typically in a single location.
If the shooter died or was hurt from injuries sustained during the incident, he is included in the total victim count. (But we have excluded cases in which there were three fatalities and the shooter also died, per the previous criterion.)
We included six so-called "spree killings"—prominent cases that fit closely with our above criteria for mass murder, but in which the killings occurred in multiple locations over a short period of time.
The auther does a horrible job. He takes it as an assumption that the reader doesn't know statistics, and when he gets to the actual meat he just states as fact, "i calculate k=32.5 m/j" " what does this mean? It means I'm right" he should as a minimum either assume completely that the reader knows everything nessesary to interpret the hypothesis test or actually make an effort to explain to layman what the p-value means.
Kudos to the author for attacking the question this way, it's always important to look at data and try to model it. (and it's a lot of work!)
Unfortunately, I'm pretty sure there's a fatal flaw in the analysis.
Suppose we had two types of years, both following a Poisson Distributino, but one with a higher incidence, the other with a lower incidence, and they alternated[1].
Now sample each type of year separately. Each will give you a Poisson distribution. To get the distribution of all years you'd just add bins of the two types together.
The sum of two poisson distributions is a poisson distribution (with a different mean), therefore, we cannot conclude anything about how the mean value is changing with time (and thus, answering the question: is the incidence rate rising) unless we actually bin the data by year, and see if the mean value is changing with time.
Unfortunately, by splitting time up, we reduce the already small sample sizes for each bracket. Time series analysis is a more appropriate tool to tackle this question.
[1] This is unchanged if the rate is continuously increasing, the setup was so that you can actually think of collecting the same data over multiple years.
"If mass shootings are really occurring at random, then this suggests that they are extreme, unpredictable events, and are not the most relevant measure of the overall harm caused by gun violence."
In my Undergrad years I would get crucified for arguing that a computational model works and concluding that it is therefore the way reality works.
Seriously though, can anyone reading this fathom a way to formalize the event "Guns are available"? What's the probability of getting a gun if it's not available in shops? You need to model a different country for that.
The same reasoning can be used to show that the probability of a mass shooting given the availability of guns is lower given a lack thereof. In other words, this: http://www.youtube.com/watch?v=KsN0FCXw914 .
And if they are indeed rare events, what's the metric for that? If we have a chance of stopping a rare, unexpected event that would add quite a lot to the expected value of deaths per year, would it not matter significantly in our efforts of stopping it?
I don't think the author is attempting to imply anything other than "Assuming mass shootings are random unrelated events, 7 mass shootings in 1 year does not necessarily signal a significant change from the past 30 years. (Though if it happens again, it does.)"
I thought so too until I read the last 3 paragraphs. "Those numbers check out" is totally valid. But concluding with the relevance of the measure of gun harm is an observation about reality, not Statistics, which is debatable, but has no relevance to what was previously mentioned.
We haven't yet defined the goals. Unless "Minimum amount of gun-related deaths" is the goal (clearly, it isn't that simple in this country), in which case his highlighted claim is definitely false - we don't know much about effective metrics. Are the psychological effects of a mass shooting similar to a snowball effect? Maybe in the long run? There's a lot more to research before saying 'insignificant', especially if you don't describe the model.
One more thought: could you define 'mass shooting'? Usually the media is responsible for that definition, whereas a random murder isn't called that.
The conclusion about the relevance of the measure of gun harm seems to me the "mass shootings in 1 year does not necessarily signal a significant change from the past 30 years" part. It means that discussions along the line of "Why the change?", or "How can we go back to the way it was before?" are premature, though it does not say anything at all about discussions along the line of "How do we reduce mass shootings?".
Mother Jones probably did a pretty decent job of defining 'mass shooting', I assume they errored on the side of inclusion (I only recall 2 this year). The authors analysis seems to make it pretty clear it is only considering that definition.
I'm really not reading this as an attack on discussions of gun violence in general, as it seems you are.
> If we have a chance of stopping a rare, unexpected event that would add quite a lot to the expected value of deaths per year, would it not matter significantly in our efforts of stopping it?
I wouldn't characterize the number of deaths via mass shootings as "quite a lot". It's probably in the same ballpark as death by lightning strike (~50/year, according to Wikipedia).
Beware: the whole point of this is article (and train of thought) is to cast a shadow of doubt over gun control. It's to remind us how these are random and extreme events. Yes, mass-shootings are random and extreme. A layperson can conclude this without having to look at any statistics.
But unfortunately this distracts from the real problem. Machine guns. And how they're legal, and easy, for anyone to buy. And ammo. And modifications for guns.
When the constitution was written to allow citizens the right to bare arms, the only arms in the legislators' wildest dreams took a minute to load one bullet, likely would miss, and probably wouldn't kill with one shot. Since the world is very different today, shouldn't the laws change too? Look at the success of gun control in the United Kingdom.
Enough of this nonsense. It reminds me of climate change deniers pointing out "Yeah but it's snowing now."
I think a better methodology would be using linear time clusters and measuring the possible impact of the Werther Effect.
Look at the regional areas where the news may not have spread out.
Look at the attempts that were stopped and see if they clustered. The stopped attempts are probably a better indicator as people, after hearing the news, are naturally more alert to the indicators that something may happen.
The other problem with the data is that there is no way, from looking at the graph, if an event happening in December affected an event happening in January, thus delimiting by years is arbitrary.
The question probably requires a more detailed treatment.
For example, even the distribution of killings by frequency looked poisson, if the number were uniformly increasing year by year, it would look like a trend.
Statistician here. Saying nothing about the substance of the argument or whether their data source appropriately classifies what counts as this kind of crime, the methodology is on the right track but not optimal.
Of course binning the events by year throws away data about specific timing. Having actual event times would allow fitting a hazard rate model.
There are two simple alternative hypotheses - explanations for a deviation from the Poisson assumption. What they're calling "random" is really "occuring at a homogeneous rate;" so we have to ask - as opposed to what?
1) clustering/overdispersion, because the events happen more often alongside each other (copycat effect or whatever; risk of a new event is a function of time since last event)
2) secular trend (the rate of events is changing over time)
We can't really distinguish between these two without explicitly modeling, and it doesn't look like we have enough data to do that. The tool to do it would be a generalized linear model with an overdispersed Poisson dependent variable.
It's kind of bad form to estimate the Poisson mean from the data, and then use that to fit the distribution you're testing against. You're using the data twice, so the p-value isn't what you think it is.
You should be conditioning on the total number of events in the sample.
Also, chi-square distribution comparison is for large samples. This is a meh-kinda-borderline-midsize sample, to use a technical term.
The test they want that has neither of these problems is Fisher's exact test for equal proportions.
If the events were generated by a Poisson process, the number in each year would be conditionally binomial, and they'd add up to the total observed event count. The test is: is the data explained by all the years getting events randomly at the same rate (null hypothesis) vs. each year having its own rate (alt hypothesis).
And finally, yes, you get a p-value. But you also need to think about the power of the test detect an anomaly if there was one (type II error). For something like this, you could do power analysis by a simple simulation, but you'd need to specify what kind of anomaly you'd want power to detect (e.g. all events cluster together in one year, to pick an extreme).
Otherwise, all you have is a design that has a correct p-value. If you reject the null hypothesis at 5%, but you have low power, you might as well toss a coin and declare the data "nonrandom" 5% of of the time. This might be as good a test as we can get with the data available, but p-value isn't the only thing you can look at.
I have flagged this article; is not only link bait using the subject everyone is talking about; is being extremely disingenuous using statistics about a so ambiguous concept as "mass shootings" to draw conclusions about a real world situation.
If you actually understood how a Poisson process works and how a hypothesis test works you would understand that his conclusions are very, very much important.
I'd say if you are going to learn about or do any kind of serious science, resist putting labels left and right just because you are tired, on this site and elsewhere. There's nothing wrong with humanities in terms of being able to benefit from applying CS to them.
1) Yes, we can use the chi-squared test here - the small number of events is built into the p value.
2) No, we do not need to include all murders, as we are not testing for murders. We are testing for mass shootings. This line of reasoning is the same as saying we cannot test for rotten apples only, we can only test if all fruit is rotten. Statistics on categories is acceptable and meaningful if apples are a specific kind of fruit, or mass shootings are a specific kind of crime. We can't draw an conclusion about crime, but we can draw a conclusion about mass shootings.
3) These statistics prove only a single thing: mass shootings in USA are likely random events and have a mean value of ~2.
And now we return you to our regular statistics hate...EDIT: Or not - nobody is questioning the real possible problem here: the data itself?
http://www.bradycampaign.org/xshare/pdf/major-shootings.pdf
This seems to imply there are FAR more mass shootings per year than indicated by the data. None of my conclusions above are correct if the data itself is wrong, and I don't even live in the USA so I can't vouch for the correctness of the data.