If you have been reading my other blogs, you may feel that I deal in "fuzzy logic". That may be true and that is the idea behind this blog.
This will take several blogs to get my idea across and I know it. My education has revolved around concepts like Newton's "Laws of Motion". We are talking about concepts like F=MA. If you are not familiar with that basic simple equation, you need to do some home work. It is easy to get ones mind around F=MA since it has very specific variables and produces very specific answers every time. What I am trying to get across is that our schools and education system revolve around "exact" answers for everything. The tests you take in school demand a single "correct" answer and leave no room for "almost" answers "close enough" answers. When you think about the world that we all live in, we find that there are very very few "exact" answers for anything. When you drive your car and look down at the speedometer and read 58 mph, are you really going "exactly" 58 mph? It might be close, but it is not "exact". When we watch a football game on TV and one team ends up with the highest score, is that team the "best" team? What if they played 10 or 20 games, how do you think they would come out? When you are asked what team will win on Sunday, you know that you can not be "sure", but you can be "close". Further, some people can pick the winner much more often than others. How do they do it? Do they use concepts like Newton's Laws or some kind of "fuzzy logic" that they themselves don't fully understand. Now we are getting to the idea behind "fuzzy logic". It looks a lot more like "common sense". Do you think that a person with a PhD in Advanced Math with out much knowledge of football could pick winners better than your buddy down the bar? I don't think so.
A little background. When I talk about groups of people who drop out of high school as being a drag on the economy, I get a lot of blow back from liberals who claim that they know of a high school drop out who has become a millionaire. The group that I am talking about is not an "exact" group with uniform characteristics, it is kind of "fuzzy". If we are prevented from dealing with or talking about groups like this, it greatly limits how us humans can deal with inexact data or situations. If we can agree on ways to deal with and discuss groups and interactions between groups that are not "exact" it would greatly increase our ability to use knowledge that is out there, but is not being taken advantage of. Hunters-gatherers have been operating with "fuzzy" data for thousands of years. If they had not, I am not sure that you and I would be here today.
Are you starting to see that we need to open our eyes to "fuzzy logic" and not limit our minds to just dealing with "exact" data? I will keep working on this and will have more blogs.
PS---Do some homework by looking up "scatter grams" where data is plotted but does not follow a single line. If the points are scattered all over the place, does that mean there is no useful data shown in the chart? How about correlations and curve fitting or conventional statistics? Think about how difficult it was for mathematicians of the day to accept Bayes theorem as true and acceptable.
This will take several blogs to get my idea across and I know it. My education has revolved around concepts like Newton's "Laws of Motion". We are talking about concepts like F=MA. If you are not familiar with that basic simple equation, you need to do some home work. It is easy to get ones mind around F=MA since it has very specific variables and produces very specific answers every time. What I am trying to get across is that our schools and education system revolve around "exact" answers for everything. The tests you take in school demand a single "correct" answer and leave no room for "almost" answers "close enough" answers. When you think about the world that we all live in, we find that there are very very few "exact" answers for anything. When you drive your car and look down at the speedometer and read 58 mph, are you really going "exactly" 58 mph? It might be close, but it is not "exact". When we watch a football game on TV and one team ends up with the highest score, is that team the "best" team? What if they played 10 or 20 games, how do you think they would come out? When you are asked what team will win on Sunday, you know that you can not be "sure", but you can be "close". Further, some people can pick the winner much more often than others. How do they do it? Do they use concepts like Newton's Laws or some kind of "fuzzy logic" that they themselves don't fully understand. Now we are getting to the idea behind "fuzzy logic". It looks a lot more like "common sense". Do you think that a person with a PhD in Advanced Math with out much knowledge of football could pick winners better than your buddy down the bar? I don't think so.
A little background. When I talk about groups of people who drop out of high school as being a drag on the economy, I get a lot of blow back from liberals who claim that they know of a high school drop out who has become a millionaire. The group that I am talking about is not an "exact" group with uniform characteristics, it is kind of "fuzzy". If we are prevented from dealing with or talking about groups like this, it greatly limits how us humans can deal with inexact data or situations. If we can agree on ways to deal with and discuss groups and interactions between groups that are not "exact" it would greatly increase our ability to use knowledge that is out there, but is not being taken advantage of. Hunters-gatherers have been operating with "fuzzy" data for thousands of years. If they had not, I am not sure that you and I would be here today.
Are you starting to see that we need to open our eyes to "fuzzy logic" and not limit our minds to just dealing with "exact" data? I will keep working on this and will have more blogs.
PS---Do some homework by looking up "scatter grams" where data is plotted but does not follow a single line. If the points are scattered all over the place, does that mean there is no useful data shown in the chart? How about correlations and curve fitting or conventional statistics? Think about how difficult it was for mathematicians of the day to accept Bayes theorem as true and acceptable.
