Science: April 2008 Archives

Previously we briefly introduced the Drake Equation which attempted to estimate the number of advanced civilizations in our galaxy. Unfortunately, the parameters going into the formula are wildly speculative, and thus so is the final result. Nevertheless, Drake himself estimates the number at 10,000, and this is the estimate we shall use.

But for all man’s effort, we’ve discovered nothing. Why not? The disparity between the huge numbers of expected contacts and the reality of finding nothing raises the Fermi Paradox — the contradiction between the high (claimed) probability of abundant life elsewhere and our complete failure to find any traces of its existence, current or in the past.

Some argue in the inherent nature for civilizations to destroy themselves or others, and thus don’t last very long — as soon as a society becomes intelligent, it comes to a rapid end. Of course, we don’t have any data so it’s pure speculation. Others say we haven’t looked long enough, and sooner or later we’re bound to find something.

But all these theories ignore the basic issue — nothing has been found, and it should be.

You see, if evolution is true, life in the universe should be abundant (or at least we shouldn’t be alone). You can’t say various planets are inhospitable to life — to our life perhaps, but not life adapted to the unique circumstances on that planet. So where is this abundant life in the universe? It appears we’re all alone.

The Drake Equation originated in 1961 as an exercise to consider how many possible intelligent societies exist with the ability to communicate with us. It’s not so much an exact formula as a thought experiment — as we shall see many of the parameters are wild guesses, so just about any value is possible. Here’s Drake’s equation:

N = R_* ∙ f_p ∙ n_e ∙ f_l ∙ f_i ∙ f_c ∙ L

• R_* — The average rate of star formation.
• f_p — Fraction of those stars which have planets.
• n_e — Average number of planets which can support life (per star).
• f_l — Fraction of n_e which actually develop life.
• f_i — Fraction of f_l which actually develop intelligent life.
• f_c — Fraction f_i which communicate outside their planet into space.
• L — Length of time signals estimate from planet (or the time a society lives).

Current Values

According to the SETI League, Drake’s current estimates provide N=10,000 — a very large number which accounts for SETI’s ambitious attempts to find other life near us. But it’s obvious the actual number is a huge approximation — so much so the actual number N is meaningless (In fact, how you perceive N can reveal bias in critical thinking, but that’s a topic for another time).

Problems

Most of the parameters are wild guesses, so let’s simplify a bit with the star and planet parameters to get the following simplified version:

N = L/1000

Where “L” is the length of time a civilization exists. Let’s assume all the other parameters are known (and agreed upon) entities — what parameter do we put in for L? If you’re optimistic, a civilization could last a long time. But if you’re pessimistic, civilizations destroy themselves rather quickly. Since we have no concrete data on L, it’s a wild guess (and thus, so is N by extension).

But it’s not so much the value for N which is interesting, but Drake’s current estimate of 10,000. The question becomes why can’t we find any evidence for life anywhere else but earth? Forget communicating with any of the existing 10,000 other societies, why can’t we find any evidence of life, anywhere, anytime?

Why have we found nothing? We’ve stumbled into the Fermi Paradox which will be the subject of a future article, as well as how all this relates to the Bible, Christians and Evolution. The Drake equation itself isn’t very interesting (other than as a thought experiment) due to it’s huge approximation, but the problems and areas it leads to are — it’s an important concept leading to scientific and theological issues which we’ll discuss next time.

References

• Drake Equation Calculator
• Drake Plaque
• SETI

There are lies, dammed lies, and statistics. (Mark Twain)

I’m reminded of a story about newspaper reporting in the old Soviet Union (I don’t know if it’s true or not, but it illustrates a point well). A car race between the United States and the Soviets ended with the United States car in first, and the Soviet car second (you should also know only two cars were in this race). But the reporting in the Soviet Union stated the Soviet car came in second, while the United States car came in second to last. Perfectly true, and yet perfectly misleading.

You must be careful with statistics. For example, it’s possible the air in your room right now could spontaneously all move in the same direction at once, piling up in the other side of the room leaving you gasping for air. Possible, yes. But when calculated, the probability is so small as to be reasonably rounded off to zero (it’s not going to happen, so breathe easy).

A similar argument against evolution applies to the probability of events occurring which result in new species (mutations, natural selection and spontaneous generation). That probability is zero (when rounded off reasonably). It’s mathematically possible, but the expectation is so low we logically round it down to zero and state the event is never going to occur.

So the evolutionist has a problem — the odds of evolution occurring are zero. One tactic evolutionists attempt to show the theory isn’t ridiculous (i.e. mathematically impossible) is showing highly improbable events happen all the time — unfortunately, it’s usually through a misapplication of statistics. You see, simple logic and common sense tell you if (as they claim) improbable events happen frequently one of two situations is most likely true.

1. The event really isn’t that improbable. Thus, our mathematical calculation of statistical odds is incorrect — an error in math has been made.
2. Statistics have been misused or misunderstood, similar to our car race example. The facts and math are correct, but the application of that knowledge is wrong.

Common sense explains the argument is already wrong, but we can continue with a specific example and explain exactly why it’s wrong. One of the methods the evolutionist uses draws false conclusions from a deck of cards — a mistake even a college professor can make; consider the following discussion from a professor of mathematics at Temple university.