One of the immediate questions that may arise is "How on earth are you going to predict if someone is going to get a divorce?".
So, what essentially i am trying to do here is to model life and its uncertainties with Mathematics...Now, can this be possible?
Certainly there are hundreds of factors that could play a role in getting a divorce. A questionnaire of a 100 -or less- questions cannot capture the facts of a person's life. But my goal is to just give it a try and see how it goes. Perhaps tens or even hundreds of thousands of answers may be able to give us a clue as to what is happening.
Each rule extracted (see previous post about what i mean by rules), will be tested for its statistical validity through chi-square tests and making adjustments through Bonferroni correction. Several other techniques will be used to assess the quality of the extracted models. In other words, if there is something there, we will find it.
Once a model is produced and is reasonably accurate, we will be ready to predict unseen cases. In other words -and continuing our divorce example- if a model is 80% correct in predicting whether someone will get a divorce, then anyone that fills the questionnaire at the end of the process, will also find out about the probability of getting a divorce. More importantly : Why he or she, is likely to get one.
So, what essentially i am trying to do here is to model life and its uncertainties with Mathematics...Now, can this be possible?
Certainly there are hundreds of factors that could play a role in getting a divorce. A questionnaire of a 100 -or less- questions cannot capture the facts of a person's life. But my goal is to just give it a try and see how it goes. Perhaps tens or even hundreds of thousands of answers may be able to give us a clue as to what is happening.
Each rule extracted (see previous post about what i mean by rules), will be tested for its statistical validity through chi-square tests and making adjustments through Bonferroni correction. Several other techniques will be used to assess the quality of the extracted models. In other words, if there is something there, we will find it.
Once a model is produced and is reasonably accurate, we will be ready to predict unseen cases. In other words -and continuing our divorce example- if a model is 80% correct in predicting whether someone will get a divorce, then anyone that fills the questionnaire at the end of the process, will also find out about the probability of getting a divorce. More importantly : Why he or she, is likely to get one.
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