Inductive argument

inductive argument.. this is my presentation to my subject scientific reasoning and critical thinking

1. Critical Thinking Inductive Reasoning

2. Introduction Inductive Argument : an argument in which the premises are intended to provide support, but not conclusive evidence, for the conclusion. Strong Inductive Argument : an inductive argument in which the premises actually do make the conclusion more likely to be true (rather than false). Remember, strength comes in degrees

3. Inductive Generalizations Generalization : statement made about all or most members of a group. Inductive generalization : inductive argument that relies on characteristics of a sample population ( i.e., a portion of the population) to make a claim about the population as a whole . i.e., an inductive argument with a generalization as a conclusion. Example: All the bass Hank caught in the Susquehanna have been less than 1lb. So, most of the bass in the Susquehanna are less than 1lb .

4. Making Inductive Generalizations stronger by making conclusions weaker. Notice… All the bass Hank caught in the Susquehanna have been less than 1lb. So, all of the bass in the Susquehanna are less than 1lb. ..is a pretty weak argument. Even if Hank fishes often, the Susquehanna is a big river and his catches are not enough to justify such a “sweeping conclusion.” However, if we changed the conclusion to “ most of the bass are…” or, better yet, “ many of the bass are…” the argument would be much stronger.

5. Statistical Arguments Statistical arguments go “the other way.” They take generalizations and draw conclusions about smaller samples of the population (usually individuals). Example : You’re a college student 90% of college students want no cumulative final. So you probably don’t want a cumulative final. The more “broad” the conclusion the better. The higher the original percentage, the better. Usually, if the percentage is around 50%, we will call the argument unreliable , even if it is more likely than not that the conclusion is true. A “rule of thumb”: if it is would reasonable to bet on it, then it is reliable.

6. Reference Class The reference class is the group to which statistics apply. As a rule, the more specific the reference class is, the better the argument is. A statistical argument can be used to support a conclusion about a group rather than an individual. 90% of college students are in favor of not having a final exam. So, 90 % of 21 students are in favor of not having a final exam.

7. In a statistical argument, if you find out more information about the person in question, you “narrow” the group (class) the person is in. Example: You are a college student who likes essays. 85% of college students who like essays want cumulative fails. Thus you probably want a cumulative final. This additional information weakened our justification for believing that you don’t want a final. Reference Class

8. Argument by Analogy Analogy : comparison of things based on similarities. Argument from analogy : an argument that suggests that the presence of certain similarities is evidence for further similarities. Common Form: A and B have characteristic X A has characteristic Y So B probably has characteristic Y too. Example : Tiffany and Heather are both tall and play basketball. Tiffany also plays volleyball. So, Heather probably plays volleyball too .

9. Evaluating Arguments from Analogy Squirrels and rats are rodents of similar size and appearance. Rats cause problems in the city, and squirrels cause problems in the suburbs. Rats should be exterminated. So, squirrels should be exterminated. Is this a good argument?

10. Evaluating Arguments from Analogy Tiffany, Heather, Amber and Krissy are all tall and play basketball. Tiffany, Amber and Krissy also play volleyball. So, Heather must also play volleyball. Sample size strengthens an argument

11. Jimber Atienza Thank you