Multiple regression - a term usually only understood by mathematical people. The purpose of multiple regression is to learn more about the relationship between several independent variables and a dependent variable. For example, the price of a property (the dependent variable) may depend on independent variables such as location, size, number of bedrooms, type of housing, etc.
Thus, the equation can be listed as such:
Y = a + b1X1 + b2X2 + ....... + bnXn
where X = the independent variable, and b = how much each independent variable contributes to the dependent variable.
Now, this is not an entry about the technicalities of multiple regression. I was just thinking, life can actually be defined by a multiple regression equation. Or rather, to be more precise, an infinite multiple regression equation. Say, life = L. The equation would then be:
L = c + d1Y1 + d2Y2 + ........ + dnXn
where each Y is, by itself, a multiple regression equation, and d has the same meaning as b above, which is the sensitivity of the dependent variable to the independent variable.
So as an example, some examples of the Y variables would be family, friends, education, country, weather, health, food... basically, everything under the sky. If we were to use family, friends, and weather only as an example, it would mean that how our life is would depend entirely on these 3 variables.
Family would definitely be a major influencing factor, so the sensitivity could be very high, say, 0.8 (out of a maximum of 1). Family itself would be a multiple regression equation, with independent variables like number of siblings, sibling ranking (are you the eldest? or middle child?), whether your siblings are brothers or sisters or a mixture, how well your parents get along, how wealthy your family is, etc.
Friends could be another big factor, so let's put the sensitivity at 0.6. This dependent variable would be another multiple regression equation with independent variables like number of friends you have, how close you are to them, age of your friends, gender, bullying, etc.
Weather sounds like a ridiculous variable, but it could still affect our lives. The sensitivity would definitely be much lower, say, 0.03 - and independent variables would be how much it affects your mood (are you especially irritated when its hot?), your health (hot and humid weather makes you fall sick more easily?) etc.
As for the sensitivity (the constants d and b), each of us would definitely have different scores. And these scores are not necessarily static throughout our lives - they may change too. As we grow older, we may be less easily affected by friends, for example. This would indicate a decrease in sensitivity.
Of course, in real life, the sensitivity would have different figures depending on whether the outcome is positive or negative. In normal multiple regression, a high sensitivity would work both ways - it amplifies the outcome, no matter good or bad. But for humans, this may not be the case. A person who treats career as extremely important (high sensitivity) may not necessarily be crushed by despair if he loses his job (a negative event, which, when multiplied by the high sensitivity, would indicate a huge negative outcome). He may actually start looking for a new job with determination.
Maybe God uses some dice to pre-determine our sensitivity before we are born?
So as an example, some examples of the Y variables would be family, friends, education, country, weather, health, food... basically, everything under the sky. If we were to use family, friends, and weather only as an example, it would mean that how our life is would depend entirely on these 3 variables.
Family would definitely be a major influencing factor, so the sensitivity could be very high, say, 0.8 (out of a maximum of 1). Family itself would be a multiple regression equation, with independent variables like number of siblings, sibling ranking (are you the eldest? or middle child?), whether your siblings are brothers or sisters or a mixture, how well your parents get along, how wealthy your family is, etc.
Friends could be another big factor, so let's put the sensitivity at 0.6. This dependent variable would be another multiple regression equation with independent variables like number of friends you have, how close you are to them, age of your friends, gender, bullying, etc.
Weather sounds like a ridiculous variable, but it could still affect our lives. The sensitivity would definitely be much lower, say, 0.03 - and independent variables would be how much it affects your mood (are you especially irritated when its hot?), your health (hot and humid weather makes you fall sick more easily?) etc.
As for the sensitivity (the constants d and b), each of us would definitely have different scores. And these scores are not necessarily static throughout our lives - they may change too. As we grow older, we may be less easily affected by friends, for example. This would indicate a decrease in sensitivity.
Of course, in real life, the sensitivity would have different figures depending on whether the outcome is positive or negative. In normal multiple regression, a high sensitivity would work both ways - it amplifies the outcome, no matter good or bad. But for humans, this may not be the case. A person who treats career as extremely important (high sensitivity) may not necessarily be crushed by despair if he loses his job (a negative event, which, when multiplied by the high sensitivity, would indicate a huge negative outcome). He may actually start looking for a new job with determination.
Maybe God uses some dice to pre-determine our sensitivity before we are born?
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