STATISTICS

There are times that scientists and sociologists make statements that are maddeningly generalized. Sometimes these statements begin to have legs of their own.

I believe such a statement was made on Sixty Minutes tonight. I didn’t note the name of the man who made this statement, but he said that according to statistics, the more older brothers a man has, the more likely he is to be gay. Just like that, matter of factly, he made a statement that I believe will have legs.

The interviewer asked, “Really?”

He answered, “Really!” emphatically.

I have three older brothers. I am not gay

My little brother has four older brothers. He is not gay. Yet according to this man who was interviewed on Sixty Minutes and his statistics, I and my little brother stood a real good chance that we would end up gay. My guess is, if this man knew how many older brothers my little bro and I had, he would call us statistical aberrations for ending up as we did. Psychologists might start asking us if we were being honest about our sexuality…after all, how could statistics be wrong?

Let me explain how and when statistics can be wrong, and let’s then use this post as a sort of precursor to my series, “Why I No Longer Trust Modern Science”.

I do not have data to back me up in this instance, so I am going to be up front and tell you that the following statement is a completely wild guess.

My guess is that the statistics this man was citing were woefully unrepresentational. My guess is, his statistics are based only on families that have gay men in them, and that families of straight men were not polled. Now I understand that this is an awful large guess on my part, but you need to know that science does polls that are not representative of the whole quite often. And, quite often, statistics then become skewed toward a certain opinion, or guess, for lack of a better word.

America is inundated with statistics every day. From mortality rates to birth rates, and everything else in between, there seems to be one statistic or another attached to the events and leanings of our lives. Scientists make statistics for the possibilities, and then publish their findings to an eagerly awaiting audience. If this audience only knew that the statistics they are reading about might well be biased to lend authority to a theory, how much credibility would we give to these statistics?

Here is a true statistic. In a family where no one is gay, there is not a chance that anyone is gay. Some would argue that point. According to the man on Sixty Minutes, there is a real good chance that I or my brother will be gay. I say…not a chance.

Now, lest you think I am bashing homosexuals, let me explain clearly that I am not. I am merely using a readily available example of what statistics really mean, and what the “experts” sometimes claim they mean.

I realize that my family isn’t representative of all men in every family. I also realize that poles and studies are often biased in efforts to prove a presupposition. Several years ago, a study was done which claimed that homosexuality was genetic, and that a person was predispositioned to be such based solely upon his DNA. Not surprisingly, many lay people still believe this is true. I don’t know what ever happened to that “study”, but I do know that it is no longer considered valid by most scientists.

It should have been obvious from the moment the statement was made. After all, I know of several examples of identical twins where one is straight and one is gay. Identical twins share the same DNA. How would it be possible for one to be gay and not the other, if genetics dictated a person’s sexuality? Yet the story of this study showed up on the front page of many major newspapers, and for that moment, was accepted as truth. The statements made grew legs, and here we are.

Seriously, how can we go from a study which PROVES something to be true, only to find out later that it isn’t? And how can the normal person, who isn’t Einstein, figure all of this out for themselves?

Sociologists and scientists bear a heavy burden, but I don’t think they understand the exact nature of that burden. Science is a pursuit of the truth, and many scientists would tell you that truth is the burden that they bear. Here is where they are wrong. The burden they bear is that they have been raised into a position to discover the truth, and in their pursuit of it, they must remain people of honesty and integrity, never succumbing to the temptation to falsify data and discoveries. That is one huge burden, and as I said, I doubt that most scientists realize that this is the real burden they bear. The pursuit of truth is lost completely once integrity and honesty are no longer the rule and not the exception.

In my thirty-eight short years, I have seen more “studies” and “proofs” exposed as fraudulent than I care to count.

Remember the story several years ago, about how a human being had already been cloned?

What ever happened to that human being?

Beware of men bearing statistics and probabilities, for the statistics they bear often only represent what they want to represent, and the probabilities they cite are often only probabilities that have not taken into account every influencing factor.

Many scientists are as influenced today by money and prestige as they are by actual truth. Sadly, the same can be said for religion, which should be altogether different, but is not.

Where are you going to go for truth, when it seems like it’s for sale to the highest bidder?