Tuesday, April 27, 2010
Cause and Effect in Populations
Chapter 15 discusses how cause and effect can support a claim. The example given in the chapter about smoking is a good example. The claim is that smoking causes cancer. Although researchers can not directly link the cause of cancer to smoking but only link that smoking increases lung cancer there is no definite proof. There are other causes of cancer that are lifestyle choices including diet and exercise. Although there is no direct link to cancer and smoking researchers can only claim that there is a high probability of cancer if a person is smoking. This is an example of how a population that has no direct proof of result but only a high probability can lead to a cause and effect claim. I thought this was useful because although there I never thought that something like high probability and having a direct proof is different. As I read and thought about this section in the chapter I realized that there is a big difference but both methods work in supporting a claim.
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Your post was very informative about the subject. I agree that the example the book gave about smoking was a good example. That example really showed the concept of cause and effect in populations. It really helped me understand this topic. I like how you went through the details of the example and then explained how the populations with no proof and high probabilities can lead to cause and effect claims. This concept was useful to me too because it explained those experiments and the proof needed for claims. I agree that both high probability and direct proof are good methods for supporting a claim.
ReplyDeleteI really liked how you went into detail about the section you picked. I looked through a few blogs before I chose my section to write about and seeing that a few classmates wrote about this one I knew I would be able to get the information again if I didn't understand it the first time through. I appreciate you going into detail about the example; it really helped me get a little bit better of a grasp on the concept of Cause and Effect in Populations. I also realized that there is a big difference in both methods but it is nice to know that they both work when checking a supporting claim.
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