Understanding scientific reasoning:
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| Main Authors: | , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Belmont, CA [u.a.]
Thomson
2006
|
| Edition: | 5. ed. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XIV, 320 S. graph. Darst. |
| ISBN: | 015506326x |
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MARC
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| 100 | 1 | |a Giere, Ronald N. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Understanding scientific reasoning |c Ronald N. Giere ; John Bickle ; Robert F. Mauldin |
| 250 | |a 5. ed. | ||
| 264 | 1 | |a Belmont, CA [u.a.] |b Thomson |c 2006 | |
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Record in the Search Index
| _version_ | 1804135962871070720 |
|---|---|
| adam_text | Contents
Preface
xi
acknowledgments xv
Chapter
і
Why Understand Scientific Reasoning?
1.1
Why Study Scientific Reasoning?
1
1.2
Some Preliminary Examples
2
The Expanding Universe
2
Global Warming
3
Cigarette Smoking and Coronary Heart Disease
4
Summary
4
1.3
How to Study Scientific Reasoning
5
How Should We Understand Scientific Reasoning?
5
General Strategy
6
A Computer Analogy
6
Tactics
7
Reasoning as a Skill
7
Part One
Theoretical Hypotheses
э
Chapter
2
Understanding and Evaluating Theoretical
Hypotheses
і і
2.1
The Double Helix: A Case Study
11
The Three-Chain Model
12
The Two-Chain Model
15
2.2
Understanding Episodes in Science
18
The Human Context of Science
18
Exploring How the World Works
19
Finding a Problem
20
Constructing Models
20
Deciding Whether a Model Fits
20
111
iv Contents
Convincing Others
20
Spreading the Word
21
2.3
Models and Theories
21
Scale Models
21
Analog Models
21
Models and Maps
22
Theoretical Models
24
Theoretical Hypotheses
25
Theories
26
2.4
Data from the Real World
27
2.5
Predictions from Models
28
2.6
The Components of a Scientific Episode
29
2.7
Evaluating Theoretical Hypotheses
31
Evidence That a Model Does Not Fit the RealWorld
31
Evidence That a Model Does Fit the Real World
32
2.8
A Program for Evaluating Theoretical Hypotheses
34
2.9
Why the Program Works
36
2.10
How the Program Works: Three Examples
37
A Case of Negative Evidence
38
A Case of Positive Evidence
39
A Case of Inconclusive Data
40
2.11
Crucial Experiments
41
The Structure of Crucial Experiments
41
Analysis of a Crucial Experiment
43
2.12
Model Development
44
A Case of Model Development
46
Exercises
47
_____
Chavter
3
Historical Episodes
58
3.1
The Phases of Venus
58
3.2
Isaac Newton and
Halley
s
Comet
63
Newtonian Models
63
Halley
s
Comet
66
3.3
The Downfall of the Phlogiston Theory
67
3.4
Darwin and Evolution
69
Special Creation
70
Darwin s Finches
70
Darwin s Model of Evolutionary Development
72
3.5
Mendelian Genetics
75
Mendel s Original Experiments
75
Mendel s Model
76
The Backcross Test
78
Contents
3.6 The Revolution in
Geology
80
Mobilism
81
Seafloor
Spreading
82
Magnetism, Geomagnetism, and Paleomagnetism
83
Exercises
86
Chavter
4
MARGINAL SCIENCE
92
4.1
Freudian Psychology
93
Freud s Theory
93
The Case of Little Hans
94
Freud s Hypothesis
95
4.2
Astrology
96
The Predictions Are
Migue
98
There Are Multiple Predictions
98
Astrology as an Interpretative Framework
99
4.3
Extraterrestrial Visitation
99
An Alternative Model
100
What about the Data?
100
4.4
Reincarnation
101
In Search of Bridey Murphy
101
4.5
Extrasensory Perception
1(13
Clairvoyance
103
Speaking of Probabilitv
1 ( 14
4.6
The Burden of Proof
104
Exercises
105
Part Two
STATISTICAL AND CAUSAL HYPOTHESES
1 1 1
Chavter
5
Statistical Models and Probability
113
5.1
Why Statistical and Probabilistic Models are Important
113
5.2
The Elements of a Statistical Study
Î
14
The Real-World Population
114
The Sample
115
A Model of the Population
115
A Model of the Sample
115
Putting the Elements Together
115
5.3
Proportions and Distributions
116
Proportions
117
Variables
117
Distributions
118
vi
Contents
5.4 Simple
Correlations
119
Variables
not Correlated
120
Variables Correlated
120
Summary
122
5.5
Symmetry of Correlations
122
5.6
Strength of Correlations
124
5.7
Probability Models
125
A Probability Model
125
Simple Addition Rule
126
Simple Multiplication Rule
127
Conditional Probabilities
128
5.8
The Flippant Judge
129
The Problem
129
The Solution
130
5.9
Sampling
131
Replacement
131
Random Sampling: Two Trials
132
Three, Four, and Five Trials
134
5.10
Large Samples
137
Expected Frequency
137
Standard Deviation
137
The Value of Large Samples
141
5.11
Sampling with Unequal Probabilities
142
Appendix
143
Correlation Coefficient
143
Exercises
144
_____
Chapter
6
Evaluating Statistical Hypotheses
147
6.1
Estimation
147
Margin of Error
149
Sample Size and Margin of Error
149
Confidence Level and Margin of Error
150
Sample Frequency and Margin of Error
152
6.2
Evaluating Distributions and Correlations
152
Evaluating Distributions
152
Evaluating Correlations
152
Evidence for a Correlation
153
Lack of Evidence tor a Correlation
154
Estimating the Strength of a Correlation
156
Confidence Levels for Correlations
156
6.3
Statistical Significance
157
Statistically Significant Differences
157
Statistical Significance and Strength of Correlations
158
Evaluating Correlations: a Quick and Dirty Method
159
Contents
vii
6.4
Survey Sampling
159
The
1997-98
Health Behavior in School-Aged
Children (HBSC) World Health Organization (WHO)
Cross-National Survey
160
How the Survey was Carried Out
161
Selected Data
162
6.5
Evaluating Statistical Hypotheses
167
The Real-World Population
167
Sample Data
171
A Statistical Model
172
Random Sampling
172
Evaluating the Hypothesis
173
Summing Up
173
6.6
A Program for Evaluating Statistical Hypotheses
175
Physical Fighting
177
Weapon Carrying in Self-Defense
179
6.7
Problems with Survey Sampling
180
Nonrandom Sampling
180
Unreliability
ofinformation
181
The Exit Polls Discrepancy in the
2004
U.S.
Presidential Election
182
Appendix
184
Formula for Margin of Error
184
Formula for Statistically Significant Differences
185
Formula for Correctly Adding Margins of Error
185
Exercises
185
Chapter
7
Causal Models
196
7.1
Correlation and Causation
196
Correlation without Causation
196
Causation is not Symmetric
197
Causal Production
197
7.2
Causal Models for Individuals
198
A Deterministic Model
198
Could Humans be Deterministic Systems?
199
A Probabilistic Model
200
7.3
Causal Models for Populations
201
A Comparative Model for Causation in Populations
201
What if the Individuals are Probabilistic?
203
7.4
Effectiveness of Causal Factors
203
Effectiveness in individuals
204
Effectiveness in Populations
204
7.5
Summary: How Causation Differs
from Correlation
204
Exercises
205
VI
11 CONTENTS
Chapter
8
Evaluating Causal Hypotheses
2O8
8.1
Saccharin and Cancer
208
8.2
Randomized Experimental Designs
210
Real-World Population and Causal Hypothesis
210
Sample Data
211
Experimental Design
211
Random Sampling
212
Evaluating the Causal Hypothesis
213
Program for Evaluating Causal Hypotheses
215
Of Rats and Humans
216
8.3
Double-Blind Studies
218
8.4
Schizophrenia and Heredity
220
Combined Results from Five Recent Twin Studies
222
8.5
Prospective Designs
224
Controlling for Other Variables
226
Prospective versus Randomized Experimental Designs
229
8.6
Schizophrenia Etiology and the Dystrobrevin-Binding
Protein
1
(DTNBP1) Gene
231
8.7
Retrospective Designs
234
Nonrandom Selection of the Experimental Group
234
Constructing the Control Group
235
Controlling for Other Variables
235
Retrospective Studies and Survey Sampling
237
Effectiveness and Retrospective Studies
239
Evaluating Retrospective Studies
239
8.8
Statistical Evidence for Causal Hypotheses
241
Can Prospective Studies Prove a Causal Connection?
243
The Ethics of Experimental Design
244
New Trends in
Biomedical
Research
244
8.9
Summary
246
Exercises
247
Part Three
KNOWLEDGE, VALUES, AND DECISIONS
263
Chapter
9
MODELS OF DECISION MAKING
265
9.1
Options
265
9.2
States of The World
266
9.3
Outcomes
266
CONTENTS
IX
9.4
Values
267
Ranking
Values
267
Measuring
Values
267
9.5
Scientific
Knowledge
and Decision Strategies
268
9.6
Decision Making with Certainty
269
Highest Value Strategy
269
9.7
Decision Making with Complete Uncertainty
270
Better and Worse Options
270
Best Options
271
Satisfactory Options
271
Playing It Safe
272
Gambling
273
Gambling versus Playing It Safe
273
9.8
Decision Making with Risk
274
Expected Value
275
Is the Expected-Value Strategy the Best Strategy?
276
9.9
Modern Utility Theory
277
Ramsey s Insight
277
A Fictional Case
278
Maximizing Expected Utility
279
Von Neumann-Morgenstern
Utility Theory
280
Another Fictional Case
282
9.10
Summary of Decision Strategies
284
Exercises
284
Chapter
Í0
Evaluating decisions
289
10.1
A Program for Evaluating Decisions
289
10.2
Decisions Involving Low Probabilities
290
Oral Contraceptives and Breast Cancer
290
10.3
Decisions Involving Moderate Probabilities
292
The Smoking Decision
292
Further Considerations
295
Confronting Your Values
296
10.4
Policy Decisions with Uncertainty
297
Global Warming
297
Whose Decision is It, Anyway?
299
Exercises
299
Index
зоз
CREDITS
319
|
| adam_txt |
Contents
Preface
xi
acknowledgments xv
Chapter
і
Why Understand Scientific Reasoning?
1.1
Why Study Scientific Reasoning?
1
1.2
Some Preliminary Examples
2
The Expanding Universe
2
Global Warming
3
Cigarette Smoking and Coronary Heart Disease
4
Summary
4
1.3
How to Study Scientific Reasoning
5
How Should We Understand Scientific Reasoning?
5
General Strategy
6
A Computer Analogy
6
Tactics
7
Reasoning as a Skill
7
Part One
Theoretical Hypotheses
э
Chapter
2
Understanding and Evaluating Theoretical
Hypotheses
і і
2.1
The Double Helix: A Case Study
11
The Three-Chain Model
12
The Two-Chain Model
15
2.2
Understanding Episodes in Science
18
The Human Context of Science
18
Exploring How the World Works
19
Finding a Problem
20
Constructing Models
20
Deciding Whether a Model Fits
20
111
iv Contents
Convincing Others
20
Spreading the Word
21
2.3
Models and Theories
21
Scale Models
21
Analog Models
21
Models and Maps
22
Theoretical Models
24
Theoretical Hypotheses
25
Theories
26
2.4
Data from the Real World
27
2.5
Predictions from Models
28
2.6
The Components of a Scientific Episode
29
2.7
Evaluating Theoretical Hypotheses
31
Evidence That a Model Does Not Fit the RealWorld
31
Evidence That a Model Does Fit the Real World
32
2.8
A Program for Evaluating Theoretical Hypotheses
34
2.9
Why the Program Works
36
2.10
How the Program Works: Three Examples
37
A Case of Negative Evidence
38
A Case of Positive Evidence
39
A Case of Inconclusive Data
40
2.11
Crucial Experiments
41
The Structure of Crucial Experiments
41
Analysis of a Crucial Experiment
43
2.12
Model Development
44
A Case of Model Development
46
Exercises
47
_
Chavter
3
Historical Episodes
58
3.1
The Phases of Venus
58
3.2
Isaac Newton and
Halley
s
Comet
63
Newtonian Models
63
Halley
s
Comet
66
3.3
The Downfall of the Phlogiston Theory
67
3.4
Darwin and Evolution
69
Special Creation
70
Darwin's Finches
70
Darwin's Model of Evolutionary Development
72
3.5
Mendelian Genetics
75
Mendel's Original Experiments
75
Mendel's Model
76
The Backcross Test
78
Contents
3.6 The Revolution in
Geology
80
Mobilism
81
Seafloor
Spreading
82
Magnetism, Geomagnetism, and Paleomagnetism
83
Exercises
86
Chavter
4
MARGINAL SCIENCE
92
4.1
Freudian Psychology
93
Freud's Theory
93
The Case of Little Hans
94
Freud's Hypothesis
95
4.2
Astrology
96
The Predictions Are
Migue
98
There Are Multiple Predictions
98
Astrology as an Interpretative Framework
99
4.3
Extraterrestrial Visitation
99
An Alternative Model
100
What about the Data?
100
4.4
Reincarnation
101
In Search of Bridey Murphy
101
4.5
Extrasensory Perception
1(13
Clairvoyance
103
Speaking of Probabilitv
1 ( 14
4.6
The Burden of Proof
104
Exercises
105
Part Two
STATISTICAL AND CAUSAL HYPOTHESES
1 1 1
Chavter
5
Statistical Models and Probability
113
5.1
Why Statistical and Probabilistic Models are Important
113
5.2
The Elements of a Statistical Study
Î
14
The Real-World Population
114
The Sample
115
A Model of the Population
115
A Model of the Sample
115
Putting the Elements Together
115
5.3
Proportions and Distributions
116
Proportions
117
Variables
117
Distributions
118
vi
Contents
5.4 Simple
Correlations
119
Variables
not Correlated
120
Variables Correlated
120
Summary
122
5.5
Symmetry of Correlations
122
5.6
Strength of Correlations
124
5.7
Probability Models
125
A Probability Model
125
Simple Addition Rule
126
Simple Multiplication Rule
127
Conditional Probabilities
128
5.8
The Flippant Judge
129
The Problem
129
The Solution
130
5.9
Sampling
131
Replacement
131
Random Sampling: Two Trials
132
Three, Four, and Five Trials
134
5.10
Large Samples
137
Expected Frequency
137
Standard Deviation
137
The Value of Large Samples
141
5.11
Sampling with Unequal Probabilities
142
Appendix
143
Correlation Coefficient
143
Exercises
144
_
Chapter
6
Evaluating Statistical Hypotheses
147
6.1
Estimation
147
Margin of Error
149
Sample Size and Margin of Error
149
Confidence Level and Margin of Error
150
Sample Frequency and Margin of Error
152
6.2
Evaluating Distributions and Correlations
152
Evaluating Distributions
152
Evaluating Correlations
152
Evidence for a Correlation
153
Lack of Evidence tor a Correlation
154
Estimating the Strength of a Correlation
156
Confidence Levels for Correlations
156
6.3
Statistical Significance
157
Statistically Significant Differences
157
Statistical Significance and Strength of Correlations
158
Evaluating Correlations: a Quick and Dirty Method
159
Contents
vii
6.4
Survey Sampling
159
The
1997-98
Health Behavior in School-Aged
Children (HBSC) World Health Organization (WHO)
Cross-National Survey
160
How the Survey was Carried Out
161
Selected Data
162
6.5
Evaluating Statistical Hypotheses
167
The Real-World Population
167
Sample Data
171
A Statistical Model
172
Random Sampling
172
Evaluating the Hypothesis
173
Summing Up
173
6.6
A Program for Evaluating Statistical Hypotheses
175
Physical Fighting
177
Weapon Carrying in Self-Defense
179
6.7
Problems with Survey Sampling
180
Nonrandom Sampling
180
Unreliability
ofinformation
181
The Exit Polls Discrepancy in the
2004
U.S.
Presidential Election
182
Appendix
184
Formula for Margin of Error
184
Formula for Statistically Significant Differences
185
Formula for Correctly Adding Margins of Error
185
Exercises
185
Chapter
7
Causal Models
196
7.1
Correlation and Causation
196
Correlation without Causation
196
Causation is not Symmetric
197
Causal Production
197
7.2
Causal Models for Individuals
198
A Deterministic Model
198
Could Humans be Deterministic Systems?
199
A Probabilistic Model
200
7.3
Causal Models for Populations
201
A Comparative Model for Causation in Populations
201
What if the Individuals are Probabilistic?
203
7.4
Effectiveness of Causal Factors
203
Effectiveness in individuals
204
Effectiveness in Populations
204
7.5
Summary: How Causation Differs
from Correlation
204
Exercises
205
VI
11 CONTENTS
Chapter
8
Evaluating Causal Hypotheses
2O8
8.1
Saccharin and Cancer
208
8.2
Randomized Experimental Designs
210
Real-World Population and Causal Hypothesis
210
Sample Data
211
Experimental Design
211
Random Sampling
212
Evaluating the Causal Hypothesis
213
Program for Evaluating Causal Hypotheses
215
Of Rats and Humans
216
8.3
Double-Blind Studies
218
8.4
Schizophrenia and Heredity
220
Combined Results from Five Recent Twin Studies
222
8.5
Prospective Designs
224
Controlling for Other Variables
226
Prospective versus Randomized Experimental Designs
229
8.6
Schizophrenia Etiology and the Dystrobrevin-Binding
Protein
1
(DTNBP1) Gene
231
8.7
Retrospective Designs
234
Nonrandom Selection of the Experimental Group
234
Constructing the Control Group
235
Controlling for Other Variables
235
Retrospective Studies and Survey Sampling
237
Effectiveness and Retrospective Studies
239
Evaluating Retrospective Studies
239
8.8
Statistical Evidence for Causal Hypotheses
241
Can Prospective Studies Prove a Causal Connection?
243
The Ethics of Experimental Design
244
New Trends in
Biomedical
Research
244
8.9
Summary
246
Exercises
247
Part Three
KNOWLEDGE, VALUES, AND DECISIONS
263
Chapter
9
MODELS OF DECISION MAKING
265
9.1
Options
265
9.2
States of The World
266
9.3
Outcomes
266
CONTENTS
IX
9.4
Values
267
Ranking
Values
267
Measuring
Values
267
9.5
Scientific
Knowledge
and Decision Strategies
268
9.6
Decision Making with Certainty
269
Highest Value Strategy
269
9.7
Decision Making with Complete Uncertainty
270
Better and Worse Options
270
Best Options
271
Satisfactory Options
271
Playing It Safe
272
Gambling
273
Gambling versus Playing It Safe
273
9.8
Decision Making with Risk
274
Expected Value
275
Is the Expected-Value Strategy the Best Strategy?
276
9.9
Modern Utility Theory
277
Ramsey's Insight
277
A Fictional Case
278
Maximizing Expected Utility
279
Von Neumann-Morgenstern
Utility Theory
280
Another Fictional Case
282
9.10
Summary of Decision Strategies
284
Exercises
284
Chapter
Í0
Evaluating decisions
289
10.1
A Program for Evaluating Decisions
289
10.2
Decisions Involving Low Probabilities
290
Oral Contraceptives and Breast Cancer
290
10.3
Decisions Involving Moderate Probabilities
292
The Smoking Decision
292
Further Considerations
295
Confronting Your Values
296
10.4
Policy Decisions with Uncertainty
297
Global Warming
297
Whose Decision is It, Anyway?
299
Exercises
299
Index
зоз
CREDITS
319 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Giere, Ronald N. Bickle, John Mauldin, Robert F. |
| author_facet | Giere, Ronald N. Bickle, John Mauldin, Robert F. |
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| author_sort | Giere, Ronald N. |
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| dewey-sort | 3501 |
| dewey-tens | 500 - Natural sciences and mathematics |
| discipline | Allgemeine Naturwissenschaft Philosophie |
| discipline_str_mv | Allgemeine Naturwissenschaft Philosophie |
| edition | 5. ed. |
| format | Book |
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| id | DE-604.BV021988182 |
| illustrated | Illustrated |
| index_date | 2024-07-02T16:10:22Z |
| indexdate | 2024-07-09T20:48:51Z |
| institution | BVB |
| isbn | 015506326x |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-015203050 |
| oclc_num | 61369793 |
| open_access_boolean | |
| owner | DE-706 DE-355 DE-BY-UBR DE-11 DE-188 |
| owner_facet | DE-706 DE-355 DE-BY-UBR DE-11 DE-188 |
| physical | XIV, 320 S. graph. Darst. |
| publishDate | 2006 |
| publishDateSearch | 2006 |
| publishDateSort | 2006 |
| publisher | Thomson |
| record_format | marc |
| spelling | Giere, Ronald N. Verfasser aut Understanding scientific reasoning Ronald N. Giere ; John Bickle ; Robert F. Mauldin 5. ed. Belmont, CA [u.a.] Thomson 2006 XIV, 320 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Naturwissenschaft Philosophie Reasoning Science Philosophy Wissenschaftstheorie (DE-588)4117665-0 gnd rswk-swf Argumentation (DE-588)4002899-9 gnd rswk-swf Forschungsmethode (DE-588)4155046-8 gnd rswk-swf Naturwissenschaften (DE-588)4041421-8 gnd rswk-swf Wissenschaftstheorie (DE-588)4117665-0 s DE-604 Naturwissenschaften (DE-588)4041421-8 s Forschungsmethode (DE-588)4155046-8 s 1\p DE-604 Argumentation (DE-588)4002899-9 s 2\p DE-604 Bickle, John Verfasser aut Mauldin, Robert F. Verfasser aut Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015203050&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Giere, Ronald N. Bickle, John Mauldin, Robert F. Understanding scientific reasoning Naturwissenschaft Philosophie Reasoning Science Philosophy Wissenschaftstheorie (DE-588)4117665-0 gnd Argumentation (DE-588)4002899-9 gnd Forschungsmethode (DE-588)4155046-8 gnd Naturwissenschaften (DE-588)4041421-8 gnd |
| subject_GND | (DE-588)4117665-0 (DE-588)4002899-9 (DE-588)4155046-8 (DE-588)4041421-8 |
| title | Understanding scientific reasoning |
| title_auth | Understanding scientific reasoning |
| title_exact_search | Understanding scientific reasoning |
| title_exact_search_txtP | Understanding scientific reasoning |
| title_full | Understanding scientific reasoning Ronald N. Giere ; John Bickle ; Robert F. Mauldin |
| title_fullStr | Understanding scientific reasoning Ronald N. Giere ; John Bickle ; Robert F. Mauldin |
| title_full_unstemmed | Understanding scientific reasoning Ronald N. Giere ; John Bickle ; Robert F. Mauldin |
| title_short | Understanding scientific reasoning |
| title_sort | understanding scientific reasoning |
| topic | Naturwissenschaft Philosophie Reasoning Science Philosophy Wissenschaftstheorie (DE-588)4117665-0 gnd Argumentation (DE-588)4002899-9 gnd Forschungsmethode (DE-588)4155046-8 gnd Naturwissenschaften (DE-588)4041421-8 gnd |
| topic_facet | Naturwissenschaft Philosophie Reasoning Science Philosophy Wissenschaftstheorie Argumentation Forschungsmethode Naturwissenschaften |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015203050&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT giereronaldn understandingscientificreasoning AT bicklejohn understandingscientificreasoning AT mauldinrobertf understandingscientificreasoning |