Review of Chapter 7
Deductive arguments
An argument in which the premises attempt to PROVE the conclusion. Deductive arguments are either valid or invalid; if valid, they are either sound or unsound (All mammals give live birth. Tigers are mammals. Therefore tigers give live birth)
Valid deductive arguments
IF the premises are true, the conclusion must be true. No valid arguments can have true premises and a false conclusion or false premises and a true conclusion
Example of valid argument
Joe is taller than Bill. Bill is taller than Sam. Joe is taller than Sam.
Example of an invalid argument
Jose is taller than Bill. Bill is taller than Sam. Therefore, Sam is taller than Joe. (True premises, false conclusion). Republicans always lie. Joe is a Republican. Joe always lies. (Valid argument, but not sound because first premise is false.)
Sound vs unsound arguments
Even if an argument is valid, it may not be sound. Sound means that the premises are, in fact, true. If one or more of the premises are false, the argument is unsound.
Example of valid and sound argument
Trump was born in the U.S. You have to be born in the U.S. to be eligible for president. Trump is eligible for president
Example of valid but unsound argument
If you accept speaking fees from Goldman Sachs you are corrupt. Clinton accepted speaking fees from Goldman Sachs. Clinton is corrupt. (This is unsound because premise 1 is false; if it were true, the argument would be valid and sound)
Inductive arguments
Arguments in which the premises attempt to support the conclusion but cannot prove the conclusion absolutely. Inductive arguments are either weak or strong depending on how many good premises there are
Example of inductive argument
Most chefs like food and are therefore heavy. Angelo is a chef. Angelo is probably heavy. (If you put “all chefs are heavy,” it’d be a deductive argument; it’d be valid but unsound)
Criminal law: reasonable doubt vs possible doubt
In criminal law, the standard of proof is “beyond a reasonable doubt.” This is an inductive argument. In deductive arguments, the standard is higher: beyond any possible doubt. (All humans will die; therefore, if you are a human, you WILL die); the conclusion MUST be true if the premise is true
Argument from analogy (inductive arguments)
Argue that because X and Y share attributes, they are probably similar and you can make comparisons between them. The more attributes they are, and the more diverse the attributes are, the stronger the argument. Harry and Rashid both like rock climbing, skydiving and base jumping. Harry also likes para-gliding; it is reasonable to assume that Rashid will like it, too.
Premise analogue
The thing or person that represents the premise of the argument. The standard of comparison. In the above example: Harry
Conclusion analogue
The thing or person that represents what or who you are comparing to the premise analogue (the conclusion of your argument); In the above example: Rashid will like it, too.
Attribute of interest
The trait or quality that you are interested in, that you are positing that they share: para-gliding
Contrary analogues
If there is more than one premise-analogue who shares some of the traits (ie. rock climbing, skydiving and base jumping,) but Alejandro doesn’t share the attribute of interest with the premise analogue (para-gliding), this detracts from the strength of the argument that Rashad will like paragliding, too. Alejandro also likes base jumping, skydiving and rock climbing, but he doesn’t like para-gliding. Weakens argument that Rashid must like para-gliding
Evaluation of inductive analogies
The more similarities the analogue have, and the more diverse those similarities are = stronger argument; the more numerous and diverse the differences are = weaker argument; more premise-analogues with numerous and diverse similarities = stronger argument
Rebutting an analogy
1) Attack analogy itself as being incorrect; 2) show how they are different or 3) use another analogy to refute statement
Reasoning from the specific to the specific
Comparing two specific populations: Guns kill people. Drugs kill people. Guns are legal. Drugs should be legal.
Reasoning from specific to general
Drawing a conclusion about a whole population based on a small sample of that population: My son’s autism was cured by vitamin C; you can cure autism by Vitamin C
Reasoning from the general to the specific
Drawing conclusion about a sample population based on the population at large: Most cowboys live in the West; Jess is a cowboy; Jess probably lives in the West
Reasoning from general to general
Viewing 2 populations as similar; conclusion about one population = conclusion about the other population: most female and male prisoners have low education, are drug users and have low SES. Therefore, if drug rehab programs work with males, they should work with females, too
Correlation
When two variables are related to each other; i.e., price of gas and miles a person drives; hours you study and GPA; food and weight. Correlation does not mean causation
Positive correlation
When the two variables either increase or decrease together, it is a positive correlation. Temperature goes up and drownings go up; eat more food and weight increases; more weightlifting and more strength; less studying and lower GPA
Negative correlation
When one variable increases and the other decreases; price of gas increases and amount of miles you drive decreases; more education = less street crime
Experiment
You control the independent variable (what you are testing—the cause; exercise) and measure the dependent variable (the effect; level 0of depression) and you have both an experimental group that gets the IV (exercise) and a control group that doesn’t get the IV. MUST have treatment/experimental group AND control group.
Blind and double blind studies
Blind – when subjects don’t know who is getting the treatment and who is getting the placebo; Double blind = when neither the subjects nor the experimenter know who is getting the treatment and who gets placebo
Argument vs explanation (causal statements)
Arguments are used to prove something; causal statements (explanations) clarify the cause, why it is so: People should give to the SPCA because many dogs and cats are dying (argument). Joe gives to the SPCA because he loves animals (causal statement/explanation)
Most common errors in causal arguments
1 and 2. Post hoc and Cum hoc (Questionable cause—confusing correlation with causation) 3. Fallacy of ignorance (We assume something is the cause just because no one has proven it isn’t), and 4) slippery slope