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Although reasons are lacking for excluding other possible causes. Here is an example: “Since I came into office 2 years ago, the rate of violent crime has decreased significantly. So, the longer prison sentences we recommended are working. “(Layman, 2000: 151). There is false cause because the longer prison sentences may be a causal factor, but the simple fact that the longer sentences preceded the decrease in violent crime does not prove this. There is no doubt that other causal factors need to be considered. 

3.2.4  Slippery Slope 

 

A Slippery Slope argument, of course fallacious, has a unique structure as follows: 

 

There is a slope- a chain of causes. It is slippery. Therefore, if you take even one step on the slope, you will slide and fall all the way to the bottom. Since the bottom is a bad place to be, you should not take the first step. Slippery slope fallacy occurs when in argument, it is concluded that an event should be prevented from happening due to the belief that its occurrence will bring the occurrence of certain other events we do not want or wish to have them happen. 

 

Example: “If there is labour strike, schools will not run, pupils will stay at home, market will be closed, the economy will be affected. So, strike should not be allowed, or labour strike should be prevented or avoided” (Fadahunsi and Adegboyega, 2010: 88).  

 

The major problem with arguing this way is that unwanted events may not follow from the event that the claim advocates should be prevented. 

 

 

This fallacy is an argument which applies not only to the premise cases, but also to cases that are different in kind from those referred to in the premises. For example: someone who has observed the performance of most logic students at interviews and then concludes that the understanding of logic enhances human skill at answering questions, thus, its study must be enforced in schools. 

3.2.6  Gamblers’ Fallacy 

 

This fallacy is committed when one argues that given the sequential or the frequent occurrences of a event in series, the probability of its (the event) re-occurrence will increase. For instance: “Socrates played Ludo game 10times and he lost, therefore, the probability that he will lose the 11th game has decreased.” 

 

You need to know that the winning or losing of the game at the 11th time should be seen on 50-50 basis. The game can end in either ways for Socrates irrespective of the previous sequential frequent occurrences.