Lecture 11 Inductive Reasoning continued Flashcards
Describe The Method of Concomitant Variation
(i) Some feature F is positively correlated with a target feature G
iff (a) increases in F are accompanied by increases in G
& (b) decreases in F are accompanied by decreases in G.
(2) Some feature F is negatively correlated with a target feature G
iff (a) increases in F are accompanied by decreases in G
& (b) decreases in F are accompanied by increases in G.
Describe the fallacy of confusing correlations with causes
To simply assume the presence of a causal connection between F and G on the basis of a correlation between them is to commit THE FALLACY OF CONFUSING CORRELATIONS WITH CAUSES.
Describe the fallacy of confusing correlations with causes in standard form
G causes F
F casues G?
H is a common cause of F and G
Describe an Inductive or Statistical Generalisation
An argument is an inductive or statistical generalisation iff a generalised conclusion about the character of some class as a whole. is drawn from characteristics of a sample of the class.
Describe that Fallacy of Hasty Generalisaion
A small sample may be unrepresentative and so suggest a general characteristic which does not apply.
Describe the Fallacy of Biased Sampling
A sample may be unrepresentative due to the method of sampling having been such as to select for particular characteristics which go unnoticed.
What are the 4 steps on evaluating Concomitant Variation in Inductive reasoning
1) Are the premises True?
2) Is the sample large enough (Fallacy of hasty generalisations)
3) is the sample biased (Fallacy of biased sampling)
4) could the results be effected by another cause.
(Remember the Last Tutorial possbile variants)
Describe Pierre’s fallacy of rare events
In a large population, a non insignificant number of events will be recorded of extremely rare events.
i.e. telepathy occurs 1 in a million people. Therefore it will occur 20 times in Australia with a population of 20 million, more than 1 in each state.