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本帖最后由 凝羽欲翔 于 2010-6-5 17:26 编辑
Sorry~I'm late~
In this argument, the arguer advocates that doctors should take sex difference into account when prescribing pain medications. In support of this, the arguer cites a research showing that when injected the same dosage of kappa opioids, the women feel less pain than men but suffered for a longer time. What’s more, from the research, the arguer also draws two conclusions: (1) kappa opioids is better for women than men in pain medication; (2) the researchers should revaluate the effects of all medications on men versus women. This argument is fraught with vague, oversimplified and unwarranted assumptions.
One major assumption in short of legitimacy is the statistic number. In the experiment, the researcher only collects 28 men and 20 women and tries to trace out the sex difference in pain medication. Choosing samples in the experiments plays a key role when we do research. Generally speaking, to make the result convincing, the sample size should keep rather the same in the compared experiments while the research fails to do so. Obviously, with different sample size, the absolute numbers received from the two experiments is not comparable. Furthermore, the sample size should be large enough to avoid small probability event. In fields, such as economic forecast which is the hot spot in our society, data mining in computer science, thousands of even ten thousands of samples are needed to build model, so that the result can be close to reality. Thus, only 28 men and 20 women mentioned in the argument are far from enough. Moreover, the arguer fails to show us whether these people share the same or similar characters in other areas, such as ages, health conditions, genetic diseases, etc. Nothing more can we peek from the argument, while such information s likely to cause a bias in the result.
Another point worth considering is the arguer’s hasty generalization. We are informed that kappa opioids is good to women for pain treatment, but for men, it is another picture. However, there are no other compared experiments to show how kappa opioids gets ahead of other pain medications. What’s more, there is little evidence that kappa opioids did help in the treatment. We do not know whether there are other factors unique in women that will influence the result of the research, such as hormone, metabolic mechanism, etc. Besides, the fact that kappa opioids may be helpful in the wisdom-teeth-extraction treatment does not indicate the same promising curative effect in other pain treatment. Based on this slim information, we can never evaluate the overall performance of Discount.
To conclude, this argument is not persuasive as it stands. Before we accept the conclusion, the arguer should present more facts that kappa opioids is indeed the best choice for women in pain medication. To solidify the argument, the arguer should enlarge the sample size in the experiments and provide more research to prove the effectiveness of kappa opioids.
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一改 thx polo~发现自己忘前忘后的
In this argument, the arguer advocates that doctors should take sex difference into account when prescribing pain medications. In support of this, the arguer cites a research showing that when injected the same dosage of kappa opioids, the women feel less pain than men and the efficacy last for a longer time. What’s more, from the research, the arguer also draws two conclusions: (1) kappa opioids is better for women than men in pain medication and men should take other drugs; (2) the researchers should revaluate the effects of all medications on men versus women. This argument is fraught with vague, oversimplified and unwarranted assumptions.
One major assumption in short of legitimacy is the statistic number. In the experiment, the researcher only collects 28 men and 20 women and tries to trace out the sex difference in pain medication. Choosing samples in the experiments plays a key role when we do research. Generally speaking, to make the result convincing, the sample size should keep rather the same in the compared experiments while the research fails to do so. Obviously, with different sample size, the absolute numbers received from the two experiments is not comparable. Furthermore, the sample size should be large enough to avoid small probability event. In fields, such as economic forecast which is the hot spot in our society, data mining in computer science, thousands of even ten thousands of samples are needed to build models, so that the result can be close to reality. Thus, only 28 men and 20 women mentioned in the argument are far from enough. Moreover, the arguer fails to show us whether these people share the same or similar characters in other areas, such as ages, health conditions, genetic diseases, etc. Nothing more can we peek from the argument, while such information is likely to cause a bias in the result.
Another point worth considering is the arguer’s hasty generalization. We are informed that kappa opioids is good to women for pain treatment, but for men, it is another picture. However, there are no other compared experiments to show how kappa opioids gets ahead of other pain medications. What’s more, there is little evidence showing that kappa opioids did help in the treatment. We do not know whether there are other factors unique in women that will influence the result of the research, such as hormone, metabolic mechanism, etc. Besides, the fact that kappa opioids may be helpful in the wisdom-teeth-extraction treatment does not indicate the same promising curative effect in other pain treatment. Based on this slim information, we can never evaluate the overall performance of kappa opioids[敲错了~~].
Last but not least, the arguer mentions that the effects of all medications on men and women should be revaluated due to the result of research. However, even though there exists some difference between men and women in the treatment with kappa opioids, it does not mean that the same goes for all medications, let alone the doubt whether the experimental result is convincing.
To conclude, this argument is not persuasive as it stands. Before we accept the conclusion, the arguer should present more facts that kappa opioids is indeed the best choice for women in pain medication. To solidify the argument, the arguer should enlarge the sample size in the experiments and provide more research to prove the effectiveness of kappa opioids.
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二改 thx Ity~
In this argument, the arguer advocates that doctors should take sex difference into account when prescribing pain medications. In support of this, the arguer cites a research showing that when injected the same dosage of kappa opioids, the women feel less pain than men and the efficacy last for a longer time. What’s more, from the research, the arguer also draws two conclusions: (1) kappa opioids is better for women than men in pain medication and men should take other drugs; (2) the researchers should reevaluate the effects of all medications on men versus women. This argument is fraught with vague, oversimplified and unwarranted assumptions.
One major assumption in short of legitimacy is the statistic number. In the experiment, the researcher only collects 28 men and 20 women and tries to trace out the sex difference in pain medication. Choosing samples in the experiments plays a key role when we do research. Generally speaking, to make the result convincing, the sample size should keep rather the same in the compared experiments while the research fails to do so. Obviously, with different sample size, the absolute numbers received from the two experiments is not comparable. Furthermore, the sample size should be large enough to avoid small probability event. In fields, such as economic forecast which is the hot spot in our society, data mining in computer science, thousands of even ten thousands of samples are needed to build models, so that the result can be close to reality. Thus, only 28 men and 20 women mentioned in the argument are far from enough. Moreover, the arguer fails to show us whether these people share the same or similar characters in other areas, such as ages, health conditions, genetic diseases, etc. Nothing more can we peek from the argument, while such information is likely to cause a bias in the result.
Another point worth considering is the arguer’s hasty generalization that kappa opioids is good to women for pain treatment, but for men, it is another picture. However, there are no other compared experiments to show how kappa opioids gets ahead of other pain medications. What’s more, there is little evidence showing that kappa opioids did help in the treatment. We do not know whether there are other factors unique in women that will influence the result of the research, such as hormone, metabolic mechanism, etc. Besides, the fact that kappa opioids may be helpful in the wisdom-teeth-extraction treatment does not indicate the same promising curative effect in other pain treatment. Based on this slim information, we can never evaluate the overall performance of kappa opioids.
Last but not least, the arguer mentions that the effects of all medications on men and women should be reevaluated due to the result of research. However, even though there exists some difference between men and women in the treatment with kappa opioids, it does not mean that the same goes for all medications, let alone the doubt whether the experimental result is convincing. No one has ever found two blades of ribbon grass alike, nor can ever two medications share similar efficacy. It's a common sense that every pill has its unique characters, so it is unwarranted to generalize the mere fact of kappa opioids to all medications.
To conclude, this argument is not persuasive as it stands. Before we accept the conclusion, the arguer should present more facts that kappa opioids is indeed the best choice for women in pain medication. To solidify the argument, the arguer should enlarge the sample size in the experiments and provide more research to prove the effectiveness of kappa opioids. |
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