Posts Tagged ‘statistics’

Education: Some facts

Inferno
Inferno
Wed May 22, 2013 10:00 pm by Inferno

Education has been around since before written history. In one form or another, people have taught other people about stuff they know, and sometimes even about stuff they don’t or can’t know.

Real “education for the masses” has been around for only a relatively short time, since the enlightenment. I’ll talk about the enlightenment specifically in a future post, so I won’t lose time here on the why’s and how’s. In Austria, we owe our first real school reform to Maria Theresa, Empress of Austria, in 1775. She made education compulsory for all 6 to 12 year olds, which was really revolutionary in these days. She caught a lot of flack for that.

Today in the world, we have a total literacy rate of roughly 85%. That number is slightly higher for men (88.5% in 2011) and lower for women (79.8% in 2011). I won’t talk about this here, though I will remark that this imbalance is atrocious.

Global Literacy Rates in 2011

One will note that the highest one gets in this graph is “>97%” literacy. That might strike some as odd, but remember that there are a fair number of people who can’t go to school, for one reason or another, and there is a surprisingly big number of functional illiterates. (That is to say, people can’t read and write well enough “to manage daily living and employment tasks that require reading skills beyond a basic level.”)

Functional illiterates are often thought to make up anywhere between 3% and 99% of the population. In less economically developed countries (LEDC’s), to give them their proper term, the numbers of literacy in itself is low (26.2% for Mali in 2009, see page 174) and the percentage of those 26% being functional illiterates may also be high. More economically developed countries (MEDC’s) tend to have higher literacy rates (usually calculated as 99% for the HDI), but may have huge rates of functional illiterates. Wikipedia claims nearly 50% for Italy in 2003, to name but one example.

These estimates are almost certainly too high. Official figures estimate about 200,000 to 400,000 functional illiterates (plus about 80,000 illiterates) in Austria, so anywhere between 2.5% and 5%.

How many people enrol in school? The numbers are a tad more difficult here. We would need to differentiate between different ethnic groups in the US to do this topic justice, but I don’t have time for that. The general trend is: Whites enrol more than Blacks than Hispanics. (Note: I am using the language from the National Center for Education Statistics (NCES).)

At most 40% of the population are enrolled in preschool, generally over 90% are enrolled from ages 7 to 17. Then, the numbers drop rapidly. About 30% of the population continue some kind of tertiary education, though half of these are 2-3 year courses. Only 16% of adults are still enrolled between the ages of 22 and 24 (generally the time needed for a Masters or equivalent), compared to about 25% of the population in Finland.

Another thing is worth mentioning in this post: PISA. Arguably the most important assessment of secondary education today is the PISA study. Done every three years, it sets out to test students in three areas (Reading literacy, Mathematics and Science) in a standardized manner. Among the top five countries (well, regions really) in the last few years were almost always Finland, Shanghai, Hong Kong and South Korea.

Now I don’t have data on South Korea’s system of education, nor on Hong Kong or Shanghai, but I think it’s fairly safe to expect that these countries are strongly influenced by at least one socialist trend: Long compulsory education for everybody. It’s certainly true for Finland.

If you want to learn more about various education systems in the EU, I suggest Eurypedia.

I want to end on a slightly depressing note. Research shows (unsourced, I think I read it in Hattie 2007) that between 60-80% of learning achievement can be predicted by looking at the background of children. (Note: Pasi Sahlberg claims about 2/3rds, so my figure is fairly accurate.) Are they from a rich family? Does the family care about education? Do the parents hold at least one degree?

This is a travesty in two ways: It means that, no matter what teachers and the education system of today are doing, we will almost certainly lose a large portion of the children. I hope that we will find ways to make this better.

Second, it means that economic inequality has lasting consequences on your descendants. That’s unacceptable, or should be. Society should work towards making society more equal. All working toward a common goal… wouldn’t that be nice?

In future posts, I will be talking about teaching strategies, effectiveness of teaching, the Hattie study, the politics of education and different systems of education. I want to use this post as a starting point for these later discussions.

Faulty Premises 2

Laurens
Laurens
Sun Apr 14, 2013 5:27 pm by Laurens

In my last post I discussed some of the more common and simplistic logical fallacies. I would recommend going back through that post if you are unsure what a logical fallacy is, as this post will assume that the reader has some prior knowledge.

 

Argument from Authority

This can be a tricky fallacy because we all know that often arguments such as those put forth in research papers rely on the referencing of relevant authorities in various fields to support them. Quoting Stephen Hawking when talking about the physics of black holes, for example would not be a fallacy because he is considered an expert in that field and there is consensus among experts on much of what he says. Thus his words can be trusted to a reasonable degree.

The fallacy occurs when someone uses the authority of an individual that is not a reliable expert on a given subject. For example it would be inappropriate to use the views of an engineer to support an argument about biology. No matter how much of an expert they might be about engineering, this has no bearing on the veracity of their views on biology.

Another form of this fallacy occurs when someone appeals to the views of a relevant expert, and holds them to be true whilst ignoring the fact that there is no consensus among other experts in that field. For example one might quote a particular scientist and use them to support a particular view on the evolution of language, taking their word as truth, whilst completely ignoring the fact that many other experts disagree.

 

Quote Mining

This fallacy is similar to the argument from authority in that it uses quotations often taken from well-known figures. The difference here is that the quotation is taken out of context, or important information is left out. Take a look at this quote from Charles Darwin:

“But, as by this theory, innumerable transitional forms must have existed, why do we not find them embedded in countless numbers in the crust of the earth?”

This appears to the reader as though Darwin is saying that there is a problem with evolutionary theory—the lack of transitional fossils. Quotes like this are frequently used by creationists in an attempt to show that even Darwin had doubts about his own theory, however if one puts this quote into context, one can see that a crucial piece of information is left out:

But, as by this theory innumerable transitional forms must have existed, why do we not find them embedded in countless numbers in the crust of the earth? It will be more convenient to discuss this question in the chapter on the Imperfection of the Geological Record; and I will here only state that I believe the answer mainly lies in the record being incomparably less perfect than is generally supposed. The crust of the earth is a vast museum; but the natural collections have been imperfectly made, and only at long intervals of time.

When put into context we can see that Darwin did not view this question as an insurmountable problem with no conceivable answer, its just that the following sentences were removed to give this impression. The use of quotations in such a misleading manner can be difficult to spot (especially if one does not have access to the original material to look it up). As a general rule of thumb, one should be weary of people using quotes from experts that appear to contradict their known views or appear to be saying something extraordinary.

 

Misleading Use of Polls and Stats

Many people use stats and polls to support their arguments, however these can often give misleading results. Where possible, one should always examine these to see whether the results may have been biased in some way. Lets use an imaginary statistic to illustrate this: 7 out of 10 British people state that that British weather is miserable.

Lets say you look into this poll and find that it was only conducted among a small number of people in Northern Scotland. The first issue would be sample size; a poll that uses a small number of individuals cannot be extrapolated to be representative of an entire nation.

The second area of potential bias is in the location of the survey, Northern Scotland is generally colder than southern parts of Britain and thus it might be expected that there would be more people who are unhappy about the weather in that region. This cannot be considered representative of the entire nation.

You might also find out that the survey was conducted in mid-January when the winter is at its worst and most miserable, a factor likely to affect people’s answers on the matter. You then discover that the survey was conducted among farmers, who as a general rule spend more time outside than people in other professions—another way in which the answers might be biased.

Finally you hear that the actual question asked was “do you agree that the weather in Britian is miserable?”—when asked in this way the question is presupposing that the weather in Britian is miserable and might thus influence the answers given.

These are a few examples in which polls and surveys can be biased. It is advisable to try to ask the following questions, when presented with such results:

  • Was the sample size large enough to be representative?
  • What factors in the method of the survey might lead it to be biased? (location, individuals asked, method of asking etc.)
  • Was the question leading or presumptuous in any way?

Of course many polls and statistics can be enlightening and are carried out in ways that eliminate bias, but it is always useful to view these results in a critical manner.

 

That’s all for now. Hopefully I have given some insight into various kinds of logical fallacy. I would be interested to hear some feedback, comments and criticisms about these posts, and ask a specific question; would you like me to continue posting about logical fallacies, or should I move on to discussing other topics?

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