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Inductive Inductive Reasoning Reasoning Concepts and Principles Concepts and Principles of of Construction Construction
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Inductive Reasoning Concepts and Principles ofConstruction.

Dec 13, 2015

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Kory Spencer
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Page 1: Inductive Reasoning Concepts and Principles ofConstruction.

Inductive ReasoningInductive Reasoning

Concepts and PrinciplesConcepts and Principles

ofof

ConstructionConstruction

Page 2: Inductive Reasoning Concepts and Principles ofConstruction.

Basic CategoriesBasic Categories

Page 3: Inductive Reasoning Concepts and Principles ofConstruction.

Basic CategoriesBasic Categories

Target - the category we are Target - the category we are interested in understanding betterinterested in understanding better

Page 4: Inductive Reasoning Concepts and Principles ofConstruction.

Basic CategoriesBasic Categories

Target - the category we are Target - the category we are interested in understanding betterinterested in understanding better

Sample - the individual or group we Sample - the individual or group we already know about or understandalready know about or understand

Page 5: Inductive Reasoning Concepts and Principles ofConstruction.

Basic CategoriesBasic Categories

Target - the category we are Target - the category we are interested in understanding betterinterested in understanding better

Sample - the individual or group we Sample - the individual or group we already know about or understandalready know about or understand

What is known about the sample may be the result of polling or experimentation.

Page 6: Inductive Reasoning Concepts and Principles ofConstruction.

Basic CategoriesBasic Categories

Target - the category we are Target - the category we are interested in understanding betterinterested in understanding better

Sample - the individual or group we Sample - the individual or group we already know about or understandalready know about or understand

What is known about the sample may be the result of polling or experimentation. In polling, this makes the neutrality and focus of questions a concern.

Page 7: Inductive Reasoning Concepts and Principles ofConstruction.

Basic CategoriesBasic Categories

Target - the category we are Target - the category we are interested in understanding betterinterested in understanding better

Sample - the individual or group we Sample - the individual or group we already know about or understandalready know about or understand

What is known about the sample may be the result of polling or experimentation. In polling, this makes the neutrality and focus of questions a concern. In experimentation, the issue is experimental design.

Page 8: Inductive Reasoning Concepts and Principles ofConstruction.

Basic CategoriesBasic Categories

Target - the category we are Target - the category we are interested in understanding betterinterested in understanding better

Sample - the individual or group we Sample - the individual or group we already know about or understandalready know about or understand

Feature in question - the property we Feature in question - the property we know about in the sample and know about in the sample and wonder about in the targetwonder about in the target

Page 9: Inductive Reasoning Concepts and Principles ofConstruction.

Using the basic categories...Using the basic categories...Will the governor cut funding for the CSU?Will the governor cut funding for the CSU?

Target - the governor’s agenda Target - the governor’s agenda (needs to be an identifiable thing)(needs to be an identifiable thing)

Page 10: Inductive Reasoning Concepts and Principles ofConstruction.

Using the basic categories...Using the basic categories...Will the governor cut funding for the CSU?Will the governor cut funding for the CSU?

Target - the new governor’s agenda Target - the new governor’s agenda (needs to be an identifiable thing)(needs to be an identifiable thing)

Sample - whatever we already know Sample - whatever we already know about his ideas about educationabout his ideas about education

Page 11: Inductive Reasoning Concepts and Principles ofConstruction.

Using the basic categories...Using the basic categories...Will the governor cut funding for the CSU?Will the governor cut funding for the CSU?

Target - the new governor’s agenda Target - the new governor’s agenda (needs to be an identifiable thing)(needs to be an identifiable thing)

Sample - whatever we already know Sample - whatever we already know about his ideas about educationabout his ideas about education

Feature in question - support for Feature in question - support for education (notice that the sample’s education (notice that the sample’s features may not correspond features may not correspond perfectly to those of the target)perfectly to those of the target)

Page 12: Inductive Reasoning Concepts and Principles ofConstruction.

Two Main Types of Two Main Types of Inductive ReasoningInductive Reasoning

Inductive generalization - intends a Inductive generalization - intends a conclusion about a class of things or conclusion about a class of things or events larger than the subset that events larger than the subset that serves as the basis for the inductionserves as the basis for the induction

Page 13: Inductive Reasoning Concepts and Principles ofConstruction.

Two Main Types of Two Main Types of Inductive ReasoningInductive Reasoning

Inductive generalization - intends a Inductive generalization - intends a conclusion about a class of things or conclusion about a class of things or events larger than the subset that events larger than the subset that serves as the basis for the inductionserves as the basis for the induction

Making this type of argument work often requires careful collection of facts, including sophisticated methods of insuring randomness of sample.

Page 14: Inductive Reasoning Concepts and Principles ofConstruction.

Two Main Types of Two Main Types of Inductive ReasoningInductive Reasoning

Inductive generalization - intends a Inductive generalization - intends a conclusion about a class of things or conclusion about a class of things or events larger than the subset that events larger than the subset that serves as the basis for the inductionserves as the basis for the induction

Analogical argument - intends a Analogical argument - intends a conclusion about a specific thing, conclusion about a specific thing, event, or class relevantly similar to event, or class relevantly similar to the samplethe sample

Page 15: Inductive Reasoning Concepts and Principles ofConstruction.

Concerns About SamplesConcerns About Samples

Is the sample representative? Is the sample representative?

Page 16: Inductive Reasoning Concepts and Principles ofConstruction.

Concerns About SamplesConcerns About Samples

Is the sample representative? Is the sample representative?

The more like one another the sample and The more like one another the sample and target are, the stronger the argument.target are, the stronger the argument.

Page 17: Inductive Reasoning Concepts and Principles ofConstruction.

Concerns About SamplesConcerns About Samples

Is the sample representative? Is the sample representative?

The more like one another the sample and The more like one another the sample and target are, the stronger the argument.target are, the stronger the argument.

Paying attention to this concern helps avoid Paying attention to this concern helps avoid the biased sample fallacy, which (like all of the the biased sample fallacy, which (like all of the inductive fallacies) results in an unusably weak inductive fallacies) results in an unusably weak induction.induction.

Page 18: Inductive Reasoning Concepts and Principles ofConstruction.

Concerns About SamplesConcerns About Samples

Is the sample representative? Is the sample representative?

The more like one another the sample and The more like one another the sample and target are, the stronger the argument.target are, the stronger the argument.

Paying attention to this concern helps avoid Paying attention to this concern helps avoid the biased sample fallacy, which (like all of the the biased sample fallacy, which (like all of the inductive fallacies) results in an unusably weak inductive fallacies) results in an unusably weak induction. induction. Self-selected samples are known Self-selected samples are known problems in this regard.problems in this regard.

Page 19: Inductive Reasoning Concepts and Principles ofConstruction.

Concerns About SamplesConcerns About Samples

Is the sample large enough? Is the sample large enough?

Page 20: Inductive Reasoning Concepts and Principles ofConstruction.

Concerns About SamplesConcerns About Samples

Is the sample large enough? Is the sample large enough?

In general, the larger the sample, the In general, the larger the sample, the better.better.

Page 21: Inductive Reasoning Concepts and Principles ofConstruction.

Concerns About SamplesConcerns About Samples

Is the sample large enough? Is the sample large enough?

In general, the larger the sample, the In general, the larger the sample, the better.better.

Paying attention to this concern helps avoid Paying attention to this concern helps avoid the hasty conclusion and anecdotal evidence the hasty conclusion and anecdotal evidence fallacies. These are both very common.fallacies. These are both very common.

Page 22: Inductive Reasoning Concepts and Principles ofConstruction.

Focus Point: Fallacy of Focus Point: Fallacy of Anecdotal EvidenceAnecdotal Evidence

Page 23: Inductive Reasoning Concepts and Principles ofConstruction.

Focus Point: Fallacy of Focus Point: Fallacy of Anecdotal EvidenceAnecdotal Evidence

The sample is small, typically a The sample is small, typically a single story single story

Page 24: Inductive Reasoning Concepts and Principles ofConstruction.

Focus Point: Fallacy of Focus Point: Fallacy of Anecdotal EvidenceAnecdotal Evidence

The sample is small, typically a The sample is small, typically a single story single story

The story may be striking The story may be striking

Page 25: Inductive Reasoning Concepts and Principles ofConstruction.

Focus Point: Fallacy of Focus Point: Fallacy of Anecdotal EvidenceAnecdotal Evidence

The sample is small, typically a The sample is small, typically a single story single story

The story may be striking The story may be striking The story is treated as though it were The story is treated as though it were

representative of the targetrepresentative of the target

Page 26: Inductive Reasoning Concepts and Principles ofConstruction.

Focus Point: Fallacy of Focus Point: Fallacy of Anecdotal EvidenceAnecdotal Evidence

The sample is small, typically a The sample is small, typically a single story single story

The story may be striking The story may be striking The story is treated as though it were The story is treated as though it were

representative of the targetrepresentative of the target Best use of the anecdote: to focus Best use of the anecdote: to focus

attention (NOT as key premise)attention (NOT as key premise)

Page 27: Inductive Reasoning Concepts and Principles ofConstruction.

Confidence and CautionConfidence and Caution

Page 28: Inductive Reasoning Concepts and Principles ofConstruction.

Confidence and CautionConfidence and Caution

As sample size grows: either As sample size grows: either confidenceconfidence increases or increases or margin of margin of errorerror decreases decreases

Page 29: Inductive Reasoning Concepts and Principles ofConstruction.

Confidence and CautionConfidence and Caution

As sample size grows: either As sample size grows: either confidenceconfidence increases or increases or margin of margin of errorerror decreases decreases

Inductions Inductions nevernever attain 100% attain 100% confidence or 0% margin of error confidence or 0% margin of error

Page 30: Inductive Reasoning Concepts and Principles ofConstruction.

Confidence and CautionConfidence and Caution

As sample size grows: either As sample size grows: either confidenceconfidence increases or increases or margin of margin of errorerror decreases decreases

Inductions Inductions nevernever attain 100% attain 100% confidence or 0% margin of error confidence or 0% margin of error

In many cases, evaluation of these In many cases, evaluation of these factors can be factors can be reasonablereasonable without without being mathematically precisebeing mathematically precise

Page 31: Inductive Reasoning Concepts and Principles ofConstruction.

Mathematical Note:Mathematical Note:Law of Large NumbersLaw of Large Numbers

While evaluation of factors relevant to the strength of an induction can be reasonable without being mathematically precise, in cases of chance-determined repetitions, more repetitions will bring alternatives closer to predictable ratios.