My last post

Back in chapter four of the Epstein book there is a short discussion of when not to repair an argument because it is unrepairable. When an argument is unrepairable it usually exhibits these similar traits outlined in the book such there being no argument, the argument has nothing to add, a premise is false, two of the premises contradict one another, the obvious premise that needed to be add would make the argument weaker, the premise needed is false, or the conclusion is false. The book gives an example of an unrepairable argument about alcoholism and how it is a disease that people can overcome within themselves but wants more treatment center to be built. The two claims that alcoholism and treatment centers should be built contradict each other, which is one of the things that makes an argument unrepairable. When an argument contradicts itself within its claim it is fair to say that the argument is no good and is unrepairable.

Margin of Error and Confidence Level

I found the discussion of margin of error and confidence level in chapter 14 interesting. It makes a lot of sense to me because I am learning about it in my stats class and I can relate to the numbers and logic that Epstein discusses in the book. An example given in the book is about an opinion poll taken by voters that had a margin of error of 2% and a confidence level of 95%. Confidence interval means in this situation that there is a 95% chance of the poll that was to be taken the next day would turn out to be 53% with a plus minus of 2% in favor of the incumbent and 47% with a plus minus in favor of the challenger. Analyzing the data we can see that there is a good chance of this happening with the estimated range given of the percent of votes since there is a 95% confidence interval. If the confidence interval was replaced with 60% then this information would not be reliable because there is a 40% chance that the data collected would be wrong.

What I learned this semester

This semester in COMM41 I learned a lot through the reading of Epstein's book, the red Group Communication book, and the exercises offered on blackboard. What I will probably take away most is the useful skill of thinking out of the box when breaking down arguments. I learned what makes a good argument and a bad argument and why they are good or bad. The group essays helped me understand my strengths and weaknesses working in a group. One of the weaknesses I learned from the group essay as well as the online posting weekly was that I tend to put things off until the final hours. It creates an unnecessary stress that could be avoided and will definitely try to improve on that. One interesting concept that I learned from the reading is the cause and effect logic of things. Even though something occurs after an event it doesn’t necessarily mean that the previous event caused it. The event that occurred after the first could have been influenced by many other things. Overall I learned how to communicate with my peers in words better than I did before this semester.

Mission Critical

The Mission Critical website was useful because it provide in depth information on the specifics of making an argument. It goes over a lot of what our Epstein book covers but with more detail and examples. I really like the way the website was set up so that it defined the concept first then gave examples. After the examples were given it also explained how the concept was incorporated into the example. The outline that the website was set up in was also very useful. It mapped out the website and where everything was clearly. The exercises that followed the short summary on the specific concepts also let me work hands on with the concept so that I could really grasp it. For me the most interesting concept that I must have missed in the reading was called Ad Hominem that the website explains how the argument is against the person. I thought reading through that was really interesting.

Cause and Effect Excercise Link

The cause and effect website reading provided a useful learning method in a concept discussed in chapter 15 of our book. I like the example given in this link because it was different from the other one in the book. It provided a secondary learning tool from the book discussing cause and effect. What I found really interesting was the pos hoc reasoning. An example that the website explains is when John feels he is about to hiccup he takes a deep breath. A bad argument would be that the hiccup causes the John to hold his breath. Although the hiccup does precede John holding his breath, it is not necessarily the cause. The cause in this situation would be John thinking he is about to hiccup. I found this interesting because it is something I never thought of but when broken down really makes sense. I learned from this reading that even though something precedes or even follows an event it is not necessarily connected by cause and effect.

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.

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.