Name as many fallacies of reasoning that you can identify in the Death Penalty article? (i.e. Ad Hominem) Review the pptx on Fallacies. No more than 200 words this is for a discussion

FALLACIES

A fallacy is a “trick” that is either a mistake in logic or an attempt to mislead through deceptive reasoning.

There are three major fallacies:

First, there are erroneous assumptions. Since assumptions are hidden or unstated, they often go be detected. Incorrect assumptions can lead a critical thinker to agree with faulty reasoning.

Second, there are distractions. Distractions are used to make irrelevant information seem relevant to the conclusion, which could lead a critical thinker to agree with faulty reasoning.

Finally, there is dependent reasoning. Dependent reasoning occurs when the support for the conclusion depends on the conclusion already being true. Failure to detect dependent reasoning can mislead critical thinkers.

COMMON REASONING FALLACIES

*Equivocation

Equivocation happens when someone tricks you into believing that different words word or phrases, which have completely different meanings, are really the same thing. You should reject the communicator’s reasoning when this occurs.

*Appeals to Authorities

Appeals to authorities are a very common form of evidence. You should be cautious when you encounter appeals to authorities. An attempt should be made to determine if the authority has a vested interest or bias. You should reject the communicator’s reasoning when they appeal to questionable authorities.

*Ad Hominem Arguments

Ad hominem arguments are arguments in which you attack a person, not their ideas. You should reject the communicator’s reasoning when this occurs.

*Ad Populum Arguments

Ad populum arguments are arguments based on popularity, not reasoning. If you grew up in New York City you are undoubtedly aware of the popular “Brooklyn Bridge” counter-argument for ad populum arguments. The child tells the parent that “everyone is going” to the party on Friday night. The parent questions that “if everyone was going to jump off the Brooklyn Bridge, would you do it as well?” You should be cautious when you encounter ad populum arguments.

*Extension Fallacy

Extension fallacies happen when the communicator’s position is extended to an unfair and unreasonable position. You should reject the communicator’s reasoning when this occurs.

*False Dilemma

False dilemmas are presented when you are purposely forced to choose between two choices. The possibility of other alternatives are never hinted at by the communicator. You should reject the communicator’s reasoning when this occurs.

*Oversimplification

Oversimplification provides fertile ground for ambiguities and assumptions. You should reject the communicator’s reasoning when this occurs.

*Confusing “what should be” With “what is”

Very often people will make assumptions about certain things and believe that they are universally held by other others. This phenomenon is also known as wishful thinking. You should reject the communicator’s reasoning when this occurs.

*Perfect Solution

We have already learned about the myth of the “right answer”. The perfect solution is similar to this concept. There is no perfect solution to any problem. The only solution that a critical thinker will arrive at is the one that conforms with their reasoning and reflects their value preferences. You should reject the communicator’s reasoning when this occurs.

*Confusing Naming With Explaining

In Sociology, this phenomenon is called labeling. Instead of investing the time to understand something we rush to hastily categorize it. If a new employee joins you at work it is natural for that person to ask questions. Suppose the new employee want to know about the supervisor. The response given is that the supervisor is “uptight.” It would be more accurate to say that the supervisor is concerned about time and leave abuse and expects total compliance with company policy. You should reject the communicator’s reasoning when this occurs.

Chapter 4: Much Ado about Practically Nothing

As we have previously stated we can use our understanding the Normal Distribution to interpret data such as IQ scores. In your text, Huff presents the example of two individuals: one with an IQ score of 98 and the other with a score of 101. If 100 is the mean, how do interpret these findings?

Well, we need to go back to the normal curve and the 95% CI, which represents the area 2 standard deviations from the mean or the area in which we believe the true mean lies. You will recall that the confidence interval is determined from the standard deviation and standard error, but that the CI gives us a unit of measurement that corresponds to the mean. In this case IQ.

So what can we conclude? Is the individual presenting with the IQ of 101 more intelligent than the individual with an IQ of 98?

To answer this question we will have to apply our critical thinking skills in the form of statistical reasoning.

An IQ test represents an individual’s performance on a test; consequently, on any given day the individual’s performance can vary.

As we have discussed before, due to the empirical rule and the normal distribution, the area 2 standard deviations from the mean indicates the probable range in which we believe the true mean or IQ lies.

Knowing these figures give more meaning to the probable error and can ensure that we do not make much ado about practically nothing. Many Peer review journals now routinely report the mean and the 95% CI, in lieu of or in addition to the standard error and standard deviation, because of its ease in interpretation. Remember the 95% CI provides us the figures that comprise the range of the upper and lower confidence interval (+/-2 sd).

Now let me refer you to the article on Confidence Intervals Box 2: (What are Confidence Intervals p 5).

Here, Ramipril was compared to a placebo. Cardiovascular events were 651 (14%) and 826 (17.8%) respectively. The relative risk was 651/826=.78, 95% CI .70-.86. The relative risk reduction (RRR) therefore is 100-78=22%. The RRR ranges from 100-70=30% to100-86=14%. (This is just an example of CI’s with a proportion rather than the mean).

Therefore the 22% relative risk reduction afforded by Ramipril could be as little as 14% or as much as 30% fewer cardiovascular events.

As Huff points out on page 58, sometimes there is much ado about practically nothing. There can be a statistical significance, but this may have no clinical or practical importance.