## Statistics Losing Ground To CS, Losing Image Among Students 115

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from the big-bad-data dept.

from the big-bad-data dept.

theodp (442580) writes

*Unless some things change, UC Davis Prof. Norman Matloff worries that the Statistician could be added to the endangered species list. "The American Statistical Association (ASA) leadership, and many in Statistics academia," writes Matloff, "have been undergoing a period of angst the last few years, They worry that the field of Statistics is headed for a future of reduced national influence and importance, with the feeling that: [1] The field is to a large extent being usurped by other disciplines, notably Computer Science (CS). [2] Efforts to make the field attractive to students have largely been unsuccessful."*

Matloff, who has a foot in both the Statistics and CS camps, but says, "The problem is not that CS people are doing Statistics, but rather that they are doing it poorly. Generally the quality of CS work in Stat is weak. It is not a problem of quality of the researchers themselves; indeed, many of them are very highly talented. Instead, there are a number of systemic reasons for this, structural problems with the CS research 'business model'." So, can Statistics be made more attractive to students? "Here is something that actually can be fixed reasonably simply," suggests no-fan-of-TI-83-pocket-calculators-as-a-computational-vehicle Matloff. "If I had my druthers, I would simply ban AP Stat, and actually, I am one of those people who would do away with the entire AP program. Obviously, there are too many deeply entrenched interests for this to happen, but one thing that can be done for AP Stat is to switch its computational vehicle to R."Matloff, who has a foot in both the Statistics and CS camps, but says, "The problem is not that CS people are doing Statistics, but rather that they are doing it poorly. Generally the quality of CS work in Stat is weak. It is not a problem of quality of the researchers themselves; indeed, many of them are very highly talented. Instead, there are a number of systemic reasons for this, structural problems with the CS research 'business model'." So, can Statistics be made more attractive to students? "Here is something that actually can be fixed reasonably simply," suggests no-fan-of-TI-83-pocket-calculators-as-a-computational-vehicle Matloff. "If I had my druthers, I would simply ban AP Stat, and actually, I am one of those people who would do away with the entire AP program. Obviously, there are too many deeply entrenched interests for this to happen, but one thing that can be done for AP Stat is to switch its computational vehicle to R."

## Statistics as standalone field (Score:5, Insightful)

Correctly applying all of these require subject matter expertise. You need to understand what you analyzing. As a result pure statistician is not very useful - generic analysis can be performed by software, in-depth analysis requires specific knowledge.

This is not unlike complaining that assembly coding is dying. Well, yes, we now have less need to code everything that way because we have better tools.

## Statistics has always had difficulty with usurpers (Score:5, Insightful)

What is concerning is how many statistical tools, each with their own set of assumptions, have blossomed up within the past few decades. There are so many stats now that stats can no longer be an ancillary to other disciplines- it needs to be given its own space and statisticians need to be given respect for their unique expertise. There is simply too much knowledge in that domain for those in more theory-driven fields to be able to claim both expertise in the conceptual models of their fields and statistics.

## Re:As a statisticians (Score:4, Insightful)

Machine learning is an example in the article. This is a blatant attack on all CS students, researchers and professors.

Let’s consider the CS issue first. Recently a number of new terms have arisen, such as data science, Big Data, and analytics, and the popularity of the term machine learning has grown rapidly.He seems to not really know CS. Statistics and probability are a tool to CS since the very inception. This is no news.

## Re:Statistics as standalone field (Score:4, Insightful)

Correctly applying all of these require subject matter expertise. You need to understand what you analyzing. As a result pure statistician is not very useful - generic analysis can be performed by software, in-depth analysis requires specific knowledge.

From my experience, statisticians tend to be far more successful acquiring subject matter expertise than people in other fields have in using proper statistical procedures for their problems.

It's like saying mathematicians are not useful because calculators. It's simply not true, and while software can perform generic analysis, it is only quite a tiny part of doing a statistical problem correctly. What we have now are coders who think that computers can set up and interpret their problems correctly, and thus we have an increase in bad results.

## Re:Statistics as standalone field (Score:5, Insightful)

## Re:Statistics as standalone field (Score:4, Insightful)

## Hard to do right, easy to not notice you're wrong (Score:5, Insightful)

I'm not very trained in statistics, but I've read more than my fair share of academic computer science papers over the years.

Even with my limited training in statistics, I've known enough to be appalled by the errant statistical reasoning used. Or even ..." The authors seemingly aren't just ignorant of how to get the answer; they often seem to have not thought through what questions they're trying to answer in the first place with their measurements and resulting statistics.

notused. I.e., "We don't know how many times to run a program to get a 'valid' average running time, so we ran it three times. Here's the average:I think a few problems come into play here:

Despite CS majors thinking we're so smart about mathematical issues, I think this might be one area where that confidence is delusional. I suspect most psychology majors who paid attention in their Experimental Design courses are more capable in the appropriate mathematics than are most CS majors.

## Re:As a statisticians (Score:4, Insightful)

## Re:Not surprised (Score:4, Insightful)

You missed the point of the lesson. The point was that you didn't have enough data to demonstrate that your model was valid. That's all.

## Re:Not surprised (Score:4, Insightful)

Take one set of data and produce two diametrically opposed answers and have them both correct? Sounds like rumor, gossip, and BS to me, not science.

No wonder there are lies, damn lies, and statistics!

Somebody missed the lecture on assumptions.