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?