1. Chapter 4: Inductive Arguments
This chapter will cover
The use of statistical evidence in arguments
The reporting of statistical data
The use of causal generalizations

2. Evidence offers strong support ‘beyond a reasonable doubt’
Inductive Reasoning
Inductive Reasoning
Evidence offers strong support ‘beyond a reasonable doubt’

3. Inductive Reasoning Likely to be true
Evidence is strong support but it is
not 100% certain.
Evidence gives weight but not certainty.

4. Inductive Reasoning Using evidence
The strength of a conclusion is based on the quality of evidence used to support the conclusion.

5. Reasoning Inductive Deductive Cycle - bump- misfire
Cycle - smooth road
- it does not misfire
Cycle – 3rd bump-misfire
Conclusion?
The horn is powered exclusively by electricity from the battery.
The battery is dead.
Conclusion?
Logically conclude that the misfiring is caused by the bumps-induction
Logically if the battery is dead the horn will not work-deduction

6. Inductive Reasoning Induction
Drawing generalizations from known facts – research, statistical evidence
Finding truth by making observations

7. Statistical Evidence Why we use statistics Control over the unknown
To make predictions and decisions
To anticipate accurate information
Connect patterns in our lives

8. Statistical Evidence Data collected by polling and research studies
Leads to
Statistical Evidence
Statistical generalizations
Data collected by polling and research studies
Gallup poll
How people vote
Harris poll
Inferences from statistical evidence

9. How Research is Done Three questions What do I want to find out?
Characteristic of interest
2. Whom do I want to know about?
Target population
3. Whom can I study to get accurate answers?
Sample

10. Sample Members of the target population Must be large enough
Must be random
Must be representative

11. Skill
Analyze the quality of statistical evidence by noting the size, representation, and randomness of the sample

12. Sample Reliability Sample size 1,000 randomly selected individuals
2. Representative
If not it is biased
3. Significant characteristics
Sometimes difficult to know
4. Biased questions
Loaded or leading questions

13. Causal Generalizations
Reasons
Eliminate difficulties
Prevent future problems
Human curiosity

14. Hume’s Method Hume’s Conditions Interpretation
1. X, the cause, preceded y, the effect, in time
2. X and y are contiguous (in contact with one another) in time and place.
3. There is a history of (1) and (2); that is, there is a history of x preceding y and of x and y being related in time and place
If one thing causes another, the cause must come before the effect
The need for a relationship in time and space between cause and effect
Chart a tendency

15. Hume’s conditions Considerations “Correlation is not causation.”
A “third-variable” could be the source of the relationship.

16. Cause and Effect Technical Causation
Necessary condition- condition must be present if the effect is present
Sufficient condition- if condition is present, effect will definitely occur

17. Stop and Think
It has been said that holding elections is a necessary but not a sufficient condition for establishing a democracy. What do you believe would be other necessary factors that would become sufficient for establishing a democratic government?

18. Mill’s Analysis John Stuart Mill Canons
Foundational to controlled studies

19. Mill’s Analysis Method of Agreement Method of Difference
X is the only factor always present when Y occurs:
Therefore, X causes Y
The only difference between (Y) happening or not is whether one element (X ) is present
If:
X is present then Y occurs
X is not present then Y does not occur

20. Chapter 4: Inductive Arguments
Checkup
Uses of statistical generalizations
Multiple causes of a problem
Problems with statistical evidence
Sample, target audience, characteristic of interest
Cause and effect- Hume and Mill’s