One Out of How Many?

There should be an image here!When deciding if the probabilities in a situation determine a choice beyond reasonable doubt, many people make the wrong decision by simply overlooking the population.

For instance, we all watch crime shows in which DNA evidence is shown to be overwhelming proof that a person accused of a crime was actually at the scene. Assume a relatively poor DNA sample is taken at a crime scene in a major city. About four hours after the crime was committed, a suspect is apprehended and the forensic evidence indicates to one part in a million that the person is guilty — or at least present at the event. This is pretty incriminating, but…

In a major city, people come and go all the time. We can ask how many people are reasonably within a four-hour radius of the crime scene. That is, of all the people on the Earth, how many can we absolutely eliminate simply because they could not have reasonably been at the scene four hours earlier? Do the estimates as many different ways as you want with as many different assumptions. I think we can agree that 10 million people being within a four-hour radius of a given scene in a major city is reasonable. It might be higher, but probably not too much lower. Then if we examined each individual, since the probability of matching to the evidence is one in a million, we expect that about 10 people will match the evidence. It might be only eight, or it could be 12, but the most likely number is 10. Let us assume one of those 10 is the criminal. The identified suspect has a probability of one in 10 of being guilty. That is a big difference from saying that the identified suspect is guilty beyond a reasonable doubt.

A similar issue comes up when assessing the probability that a person has a disease based on test results. Many medical tests are not as accurate as one would like. They have two ways of being in error: false negatives and false positives. But the test for HIV is particularly good. It has extremely high sensitivity and specificity. Knowing nothing else about a person other than that person tested positive will cause most, if not all, physicians to be certain the person is infected. Many physicians will flatly state that if you test positive, you’ve got it. No question. No room for doubt. You’ve got it. To see if that is true with an excellent test such as the HIV, consider two patients, one from a high risk group and one from a low risk group.

For both patients the parameters of the test are the same.

Sensitivity = 99.9% (Positive response for an infected person)

Specificity = 99.99% (Negative response if not infected)

One patient is from a low risk group with known infection rate of 0.01%

The other patient is from a higher risk group with a known infection rate of 1.5%

What are the probabilities that either patient has an HIV infection assuming both get a positive response?

The higher-risk patient has a probability of 150/151 of being infected — essentially a sure thing.

The low-risk patient has a probability of 50% of being infected.

If there is sufficient interest, I will post the calculations that give these results. They are simple and do not involve any high math. Hint: assume a population 10,000 people to be examined. What are the results?

The point is that by knowing the population that each person comes from, we know more information and that can change the meaning of the test results greatly. The more we know, the better we can compute the probabilities, but most people do not use all the information available to make the correct decision.

The difference in the probability of infection of these two patients is due to what we mean by random sampling. If we knew nothing additional about the patients other than the fact that they had tested positive, then we would have to use the known average infection statistics for humanity as a whole. But by adding additional information such as whether either one avoids risky sexual practices, we can remove some uncertainty.

[Photo above by Marco Bellucci / CC BY-ND 2.0]

Population Change: Another Influence On Climate Change

There should be an image here!Changes in the human population, including aging and urbanization, could significantly affect global emissions of carbon dioxide over the next 40 years, according to research results published this week.

The research, results of which appear in a paper in the journal Proceedings of the National Academy of Sciences (PNAS), was conducted by scientists at the National Center for Atmospheric Research (NCAR), the International Institute for Applied Systems Analysis (IIASA) and the National Oceanographic and Atmospheric Administration (NOAA).

It was funded by the National Science Foundation (NSF), a European Young Investigator’s Award, and the Hewlett Foundation.

“By examining the relationship between population dynamics and greenhouse gas emissions, this groundbreaking research increases our understanding of how human behaviors, decisions and lifestyles will determine the path of future climate change,” says Sarah Ruth, program director in NSF’s Division of Atmospheric and Geospace Sciences, which funds NCAR.

By mid-century it is estimated that global population could rise by more than three billion people, with most of that increase occurring in urban areas.

The study showed that a slowing of that population growth could contribute to significantly reducing greenhouse gas emissions.

The researchers found that if population follows one of the slower growth paths foreseen as plausible by demographers at the United Nations, by 2050 it could account for 16 to 29 percent of the emission reductions thought necessary to keep global temperatures from causing serious impacts.

The effect of slower population growth on greenhouse gas emissions would be even larger by the end of the century.

“If global population growth slows down, it is not going to solve the climate problem, but it can make a contribution, especially in the long term,” says the paper’s lead author, Brian O’Neill, an NCAR scientist.

O’Neill’s co-author, IIASA scientist Shonali Pachauri, says that slower population growth will have different influences, depending on where it occurs.

“A slowing of population growth in developing countries today will have a large impact on future global population size. However, slower population growth in developed countries will matter to emissions, too, because of higher per capita energy use,” says Pachauri.

Scientists have long known that changes in population will have some effect on greenhouse gas emissions, but there has been debate on how large that effect might be.

The researchers sought to quantify how demographic changes influence emissions over time, and in which regions of the world. They also went beyond changes in population size to examine the links between aging, urbanization, and emissions.

The team found that growth in urban populations could lead to as much as a 25 percent rise in projected carbon dioxide emissions in some developing countries.

The increased economic growth associated with city-dwellers was directly correlated with increased emissions, largely due to the higher productivity and consumption preferences of an urban labor force.

In contrast, aging can reduce emissions levels by up to 20 percent in some industrialized countries. Older populations are associated with lower labor force participation, and the resulting lower productivity leads to lower economic growth.

“Demography will matter to greenhouse gas emissions over the next 40 years,” says O’Neill. “Urbanization will be particularly important in many developing countries, especially China and India, and aging will be important in industrialized countries.”

The researchers worked with projections showing that population aging will occur in all regions of the world, a result of people living longer and declines in fertility.

The authors developed a set of economic growth, energy use, and emissions scenarios, using a new computer model (the Population- Environment-Technology model, or PET).

To capture the effects of future demographic change, they distinguished between household types, looking at age, size, and urban vs. rural location.

In addition, they drew on data from national surveys covering 34 countries and representative of 61 percent of the global population to estimate key economic characteristics of household types over time, including labor supply and demand for consumer goods.

“Households can affect emissions either directly, through their consumption patterns, or indirectly, through their effects on economic growth,” O’Neill explains.

The authors also suggest that developers of future emissions scenarios give greater consideration to the implications of urbanization and aging, particularly in the U.S., European Union, China and India.

“Further analysis of these trends would improve our understanding of the potential range of future energy demand and emissions,” says O’Neill.

The researchers caution that their findings do not imply that policies affecting aging or urbanization should be implemented as a response to climate change, but rather that better understanding of these trends would help anticipate future changes.

[Photo above by Arenamontanus / CC BY-ND 2.0]

Cheryl Dybas @ National Science Foundation

[awsbullet:fred pearce climate]

Which Countries Hold The Top Spots For Internet Usage?

No Surprise That China Holds The Top Spot

It is now estimated that some 1.8 billion people from around the world now have access to the Internet. The importance of the Internet has over shadowed any other medium including that of television. TV is limited to a one way presentation, whereas the Internet provides the user with a way to communicate with others from around the world. In a recent article it also stated that:

Here are some standout facts and observations that give additional perspective to the Internet usage of the top countries on the Internet.

  • There are a total of 1.8 billion Internet users in the world.
  • There are 32 countries with more than 10 million Internet users.
  • The top 10 countries on the Internet together have 1.17 billion Internet users. That’s 65% of all Internet users in the world.
  • The top 20 countries on the Internet together have 1.47 billion Internet users. That’s just under 82% of all Internet users.
  • India is the fourth largest country in terms of Internet users in spite of having an Internet penetration of a measly 6.9%. This thanks to its huge population.
  • China takes the top spot both in terms of population and Internet users. China has almost twice (1.8x) as many Internet users as the United States.
  • China together with the United States, the top two countries, make up half of the Internet users in the top 15.
  • Out of the top 20 countries, the five with the highest Internet penetration (not users) are: United Kingdom (82.5%), South Korea (81.1%), Germany (79.1%), Japan (78.2%), United States (76.3%).

By Internet penetration, we mean the share of the population made up of Internet users.

If one looks at China with a population of 1.3 billion people, it is easy to see that there is a large potential for future expansion of Internet users in that country. Whereas others countries like the U.S. may not see limited growth when it comes to Internet users. We can call China the new frontier.

Comments welcome.

Source – pingdom

Rise In Immigration May Help Explain Drop In Violent Crimes

There should be an image here!During the 1990s, immigration reached record highs and crime rates fell more precipitously than at any time in U.S. history. And cities with the largest increases in immigration between 1990 and 2000 experienced the largest decreases in rates of homicide and robbery, a University of Colorado at Boulder researcher has found.

Tim Wadsworth, an assistant professor of sociology, has tested the hypothesis, famously advanced by Harvard sociologist Robert J. Sampson, that the rise in immigration could be related to the drop in crime rates.

Wadsworth noticed Sampson’s argument in a 2006 New York Times op-ed piece. As Wadsworth recalled, “My reaction was that this is really interesting, and it’s a very testable question.”

New research supports Sampson’s hypothesis, Wadsworth reports in the June edition of Social Science Quarterly.

“Cities that experienced greater growth in immigrant or new-immigrant populations between 1990 and 2000 tended to demonstrate sharper decreases in homicide and robbery,” Wadsworth writes. “The suggestion that high levels of immigration may have been partially responsible for the drop in crime during the 1990s seems plausible.”

Drawing from the FBI’s Uniform Crime Reports and U.S. Census data, Wadsworth analyzed 459 cities with populations of at least 50,000. Wadsworth measured immigrant populations in two ways: those who are foreign-born and those who immigrated within the previous five years.

Wadsworth focused on medium and large cities because about 80 percent of violent crime takes place there. Wadsworth said distinguishing legal and illegal immigration is difficult, as the U.S. Census does not track those numbers, but he notes that immigrant citizens and non-citizens often live together in the same communities.

He tracked crime statistics for homicide and robbery because they tend to be reported more consistently than other crimes. Robberies are usually committed by strangers — which increases the reporting rate — and “homicides are difficult to hide,” he said.

Wadsworth’s findings contradict much of the public rhetoric about the relationship between immigration and crime. As the Arizona Republic reported this month, violent crime in that state’s border towns has remained essentially flat during the past decade even as drug-trade violence on the other side of the border has burgeoned.

The presumed link between immigration and crime has a long history in the United States and overseas. Wadsworth said such sentiments are often expressed on Internet blogs and elsewhere.

Wadsworth contends that looking at crime statistics at a single point in time can’t explain the cause of crime rates.

Using such snapshots in time, Wadsworth finds that cities with larger foreign-born and new-immigrant populations do have higher rates of violent crime. But many factors — including economic conditions — influence crime rates.

If higher rates of immigration were boosting crime rates, one would expect long-term studies to show crime rising and falling over time with the influx and exodus of immigrants. Instead, Wadsworth found the opposite.

Using long-term analyses, Wadsworth noted, cities that experienced the largest growth in the proportion of foreign-born and newly arrived immigrant populations experienced larger decreases in violent crime between 1990 and 2000. That finding, Wadsworth wrote, “suggests that Sampson may be right — that immigration may be partly responsible for the decrease in violent crime.”

Wadsworth’s research suggests that, controlling for a variety of other factors, growth in the new immigrant population was responsible, on average, for 9.3 percent of the decline in homicide rates, and that growth in total immigration was, on average, responsible for 22.2 percent of the decrease in robbery rates.

Exactly why growth in immigration is accompanying decreases in violent crime is hard to determine with city-level data. Some have suggested that immigrant communities are often characterized by extended family networks, lower levels of divorce, and cultural and religious beliefs that facilitate community integration. Wadsworth notes that “criminologists have long known that these factors provide buffers against crime.”

“From the late 1800s to the present, the association between immigration and crime has been a center point of anti-immigrant discourse and public policy,” Wadsworth writes. “Although there has been scant empirical research to support such claims, they have persisted with little debate.”

Tim Wadsworth @ University of Colorado at Boulder

[Photo above by Ajagendorf25 / CC BY-ND 2.0]

[awsbullet:immigration crime]

Tasmanian Devils Face The Possibility Of Extinction

I remember seeing Tasmanian devils in the old Looney Toon cartoons, but always thought that there was no such critter. If you recall the old cartoons the Tasmanian Devil was a animal that would spin at a high rate of speed destroying everything in its path. So when I read that the Tasmanian Devils were facing extinction, I stopped to read an article that describes their plight.

The article stated that:

In real life, the carnivorous marsupials are facing a deadly and mysterious disease that has been decimating their numbers since it was first reported in 1996.

In the wild, the Tasmanian devil – the largest marsupial carnivore alive – has lost about 60 percent of its population in just the last decade. Experts say that without intervention, the disease could wipe them out within 50 years.

The tumors on a Tasmanian Devil looks like this:

Has anyone seen a real live Tasmanian Devil? Are they as ferocious as the cartoons would have us believe?

Comments welcome.