PHI 1101: Lecture 4 Sept 30 2011
As noted, a deductive argument is intended to produce logically conclusive support for its conclusion.
Non deductive arguments:
An argument intended to provide probable support for its conclusion
the premises of a non deductive argument are meant to make the conclusion probable or likely
Support for the conclusion is a matter of .
Non deductive arguments can be described as successful or unsuccessful.
Three degree of probability for a successful non deductive argument:
1) if the premises of an argument make the conclusion almost certain, then we describe the argument as
successful and dispute the degree of support which the premises lend the conclusion as close to certain.
2) on the other hand, if the premises of an argument do not render the conclusion close to certain, but quite
plausible, then the argument is still successful, but we describe it as the support which the premises lend
the conclusion as very likely. ( a great deal more likely than not)
3) if the premises of an argument provide some basis for the conclusion, but no great support then it is still
successful but we describe the matter of degree upon which the premises support the conclusion as being
An unsuccessful non deductive argument:
If the degree of support that the premises give the conclusion is little of none at all, then we describe the
argument as being unsuccessful.
A non deductive argument is unsuccessful when its premises are not relevant to the conclusion or do not
adequately support the conclusion or do not provide sufficient information.
Three types of non deductive arguments:
1) Inductive Generalizations: most often with inductive generalizations, we start with premises about
individual members of a group and a reason to conclusions about the group as a whole.
The movement is from the particular to the general. So whenever we begin with observations about some member of a group, and end with a generalization
about all of them, its called an inductive generalization
Ex: “I’ve owned 2 Dell Computers and both sucked. I’m starting to think all Dell computers are crap.”
‘I got food poisoning the last time I went to that restaurant; now, I’m afraid to go back.’
More formally, an inductive generalization hasthis form:
X per cent of the observed members of group A have property P.
Therefore, X per cent of all members of group A probably have property P.
Not all examples actually mention percentages, though.
‘40 per cent of people in our survey said they support the Conservative Party. So, we expect the
Conservatives to get 40 per cent of votes in this election.’
How good is the argument:
Inductive generalizations can be ‘successful’ or ‘unsuccessful’
They can vary in strength, according to the degree of support the premises provide for the conclusion.
How well does our survey support our conclusion about the election?
That depends on how large the sample was (among other things).
How many people were surveyed? 5? 1000?
The reliability of a generalization depends partly on the size of the sample used.
Basing a conclusion on inadequate sample size: ‘hasty generalization’ Generally: the larger the sample, the more likely it is to reliably reflect the nature of the larger group.
To be useful in inductive generalization, a sample must be representative.
It must represent the target group. If it doesn’t, then it’s a biased sample.
Worst case: ‘We examined 1,000 horses. From this we conclude that no cows have mad cow disease.’
[How do 1,000 horses represent cows?]
‘Canadians are likely to vote NDP in this election. We surveyed over 1,000 union members, and they told
us . . .’
inductive generalization, sample: union members
‘Nova Scotians are strongly in favour of a freeze on tuition. We surveyed 500 university students, and they
said . . .’
To be truly representative, the sample should be similar to the target group in that it:
has all the same relevant characteristics,
and has those characteristics in the same proportion that the target group does.
Sometimes we have good, but incomplete, knowledge of some group of people or things and based on that,
we reach a conclusion about some member of that group.
‘Canada’s Parliament is overwhelmingly white and male. So, your MP is probably a white male.’
*NOTE: With a statistical syllogism the movement is from the gen