louden

Yes. Bishops in the US closed parishes in March. The Pope granted a dispensation so that Catholics do not have the obligation to attend Mass during Lent and Holy Week.

One use case I have is embedding statistical calculations in larger applications. Calling R from the language the application is written in is a lot better than rewriting the statistical calculation in that language, especially when it is a complex model.

You are comparing a program where the benefits vastly outweigh the cost to a program where the benefit is mostly speculative and the cost known.

The cost of full body imaging is not just in the scan itself but in the procedures that follow it that require anasthesia (non-zero chance of killing the patient), cause pain and may cause secondary infection. In fact, just being in the hospital or doctors office to get the procedure has a non-zero risk to due to the concentration of sick people there.

People have commited suicide because of medical test results that turned out to be wrong. A decision has to be made about how many tests are performed and under what conditions. Unfortunately, that will cause harm to people no matter where we, as a society, draw that line.

In medicine, there are physically harmless tests that can still cause harm. Full body scans are one of them. If something is found, it will likely have an emotional impact on the patient. Not all people are equally rational. Not all people have a good grasp of the statistical nature of the findings. That applies to educated people and medical professionals who deal with this stuff everyday.

My point was not that either side was correct but rather that a simple statement like "more data is always better" is not as simple as they seem to think it is. Those of us who work in this field deal with balancing the risks as best we can so that we can detect the marginal elevated risk of something in a way so that the benefit outweighs the costs (financial, physical and emotional).

More data is not always better. The collection process itself can be dangerous or unpleasant for the patient.

Several years ago I worked on a study looking at the spread of bacterial lung infections in long term hospital patient. In order to get the data, we would have to intubate patients that did not need it. In this case, the people who approve these studies rightfully ruled that getting that data would be too painful for the patients to allow.

Biopsies caused by benign findings from a full body scan are not without pain, emotional distress, risk or cost to the patient. Period. It must be weighed against the benefit that the patient would recieve (all in the aggregate, or course).

When I was learning undergraduate mathematical statistics, my professor made it a point to connect the links between linear models and many different tests.

In the back of Statistical Inference by Casella and Berger, there is a great chart making similar connections between the most common statistical distributions.

There is a lot of rhyming in statistics.

The beauty of R (and Python) is the ecosystem, not necessarily the language. Most statisticians want libraries that they can use to do the modeling so that they can focus their time on the data, not the programming.

I imagined that would be the case, but don't have the CS background to prove one way or the other. I am currently learning OCaml and would love to use it more, but my job keeps me tied to R, SAS and Python.

It is much more than a lack of maintenance. The weight of the cargo, the temperature of the road, the way the cargo is distributed in/on the trailer and manufacture defects can all contribute to blowouts of servicable tires. Those issues also make the lifespan of identical tires vary by thousands of miles traveled.

While replacing tires more frequently would reduce the number of blowouts, it would be very wasteful. In the US, DOT inspections are frequent and they look at the tires to make sure they are in good condition.

It would be nice to see the sensitivity and specificity of the technique and for humans. False positives and false negatives are not equal in medicine, so we should report in such a way that people can evaluate them.

In this type of cancer, a lower specificity is an acceptable trade off for a very high sensitivity.

Her consent would also be needed.