Chapter 4: Inductive Arguments

Copyright © 2012 Pearson Education, Inc. All rights reserved.

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


Inductive Reasoning

Inductive Reasoning

• Evidence offers strong support ‘beyond a reasonable doubt’


Inductive Reasoning

Likely to be true

• Evidence is strong support but it is not 100% certain.

• Evidence gives weight but not certainty.


Inductive Reasoning

Using evidence

• The strength of a conclusion is based on the quality of evidence used to support the conclusion.


Reasoning

Inductive

• Cycle - bump- misfire• Cycle - bump - misfire• Cycle - smooth road

- it does not misfire• Cycle – 3rd bump-misfire

Conclusion?

Deductive

• The horn is powered exclusively by electricity from the battery.

• The battery is dead.

Conclusion?


Inductive Reasoning

Induction

• Drawing generalizations from known facts – research, statistical evidence

• Finding truth by making observations


Statistical Evidence

Why we use statistics

• Control over the unknown

• To make predictions and decisions

• To anticipate accurate information

• Connect patterns in our lives




Data collected by polling and research studies

Gallup poll How people voteHarris poll

Statistical generalizations

Inferences from statistical evidence

Leads to


How Research is Done

Three questions

1. What do I want to find out? Characteristic of interest2. Whom do I want to know about? Target population3. Whom can I study to get accurate answers? Sample


Sample

Members of the target population

• Must be large enough• Must be random• Must be representative


Skill Analyze the quality of statistical evidence by

noting the size, representation, and randomness of the sample


Sample

Reliability

1. Sample size 1,000 randomly selected individuals2. Representative If not it is biased3. Significant characteristics Sometimes difficult to know4. Biased questions

Loaded or leading questions


Causal Generalizations

Reasons

• Eliminate difficulties• Prevent future problems• Human curiosity


Hume’s Method

Hume’s Conditions1. 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

Interpretation1. If one thing causes another,

the cause must come before the effect

2. The need for a relationship in time and space between cause and effect

3. Chart a tendency


Hume’s conditions

Considerations

• “Correlation is not causation.”• A “third-variable” could be the source of the

relationship.


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


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?


Mill’s Analysis

John Stuart Mill

• Canons • Foundational to controlled studies


Mill’s Analysis

Method of Agreement

• X is the only factor always present when Y occurs:Therefore, X causes Y

Method of Difference

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


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

Chapter 4: Inductive Arguments

Documents

pearson education

use of statistical evidence

quality of evidence

true evidence

statistical evidencewhy

sample copyright

leading questions copyright

reporting of statistical