Inference and intervention: Causal models for business analysis
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York [u.a.]
Routledge
2014
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | XIV, 261 S. graph. Darst. |
| ISBN: | 9780415657594 9780415657600 |
Internformat
MARC
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| 100 | 1 | |a Ryall, Michael J. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Inference and intervention |b Causal models for business analysis |c Michael D. Ryall; Aaron L. Bramson |
| 264 | 1 | |a New York [u.a.] |b Routledge |c 2014 | |
| 300 | |a XIV, 261 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Includes bibliographical references and index | ||
| 650 | 4 | |a Mathematisches Modell | |
| 650 | 4 | |a Decision making |x Mathematical models | |
| 650 | 4 | |a Decision making |x Statistical methods | |
| 650 | 4 | |a Business planning |x Statistical methods | |
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| 650 | 0 | 7 | |a Unternehmen |0 (DE-588)4061963-1 |2 gnd |9 rswk-swf |
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| 689 | 0 | |C b |5 DE-604 | |
| 700 | 1 | |a Bramson, Aaaron L. |e Verfasser |4 aut | |
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| 999 | |a oai:aleph.bib-bvb.de:BVB01-026814668 | ||
Datensatz im Suchindex
| _version_ | 1804151453897457664 |
|---|---|
| adam_text | Contents
List of
Figures
-
1л
Acknowledgments
xi
її
1
Introduction to Causal Analysis I
1 ■ 1
Situational Assessment
ι
12
Managerial Intervention
л
2
Qualitative Causal Models
2.1
Setting the Stage j5
2.2
Building a Qualitative Causal Model
і у
2.2.1
Nodes 17
2.2.2
Links jo,
2.2.3
Some Examples of Qualitative Causal Models
25
2.3
Causal Independence
31
2.3.1
Serial Triplets
32
2.3.2
Diverging Triplets
33
2.3.3
Converging Triplets
34
2.3.4
Causal Independence in General
3
Application: Interview Case Study
44
3.1
Getting Started
47
3.2
Focus on the Significant Drivers
52
3.3
Seek Sources of Common Problems
55
vi
Contents
3.4
Ask Specific Questions
59
3.4.1
Administrative Staff
61
3.4.2
Service Staff
62
3.4.3
Doctors: Generalists and Specialists
62
3.5
Bring it All Together
65
3.6
Provide Specific Recommendations
71
3.6.1
Upgrade Account Management System
71
3.6.2
Adjust to an Aging Population
73
3.6.3
Appeal to a Younger Crowd
75
3.6.4
Final Note
75
4
Quantitative Causal Models
78
4.1
Probability Basics
78
4.1.1
Variable States
78
4.1.2
Events
79
4.1.3
Probabilities
81
4.1.4
Conditional Probabilities
83
4.1.5
Joint Probabilities
84
4.1.6
System States
85
4.1.7
Bayes
Rule
86
4.2
Quantifying a Qualitative Model
86
4.2.1
More Refined Approximations
89
4.3
Working with Quantitative Models
90
4.3.1
Probabilities from Count Data
91
4.3.2
Joint Probability Tables
93
4.3.3
The Complete Advertising Model
94
4.3.4
System-Level Joint Distribution
&
Factorization
96
4.3.5
Marginalization
97
4.4
The Move to Causal Models
100
5
Situational Analysis
109
5.1
Marginal from Conditional Probabilities 111
5.1.1
Serial Connections 111
5.1.2
Diverging Connections
112
5.1.3
Converging Connections
113
5.2
Evidence
&
Inference in Causal Models
114
5.2.1
Serial Connection
115
Contents
vii
5.2.2 Divergent
Connection
121
5.2.3
Convergent Connection
123
6
Application: Modeling
Business
Financiais
132
6.1
The Spreadsheet Approach
134
6.2
Building a Causal
Model
135
6.3
Marketing Uses
the Prosecutor s Fallacy
143
6.4
Green Ink Creates Simpson s Paradox
146
7
Single-Agent Interventions
151
7.1
One Decision, No Information
152
7.2
Multiple Decisions with Information
153
7.2.1
The Extended Model
154
7.2.2
General Solution Procedure
156
8
Application: Disrupting the Taxi Business
176
8.1
An Allocation of Resources Decision
177
8.2
Price Uncertainty and Market Research
181
8.3
Competitor Legal Response
185
9
Multi-Agent Interventions
189
9.1
Elements of a Game
190
9.2
Nash Solutions
192
9.3
Causal Form Games
195
9.4
Solving Games with Causal Models
197
9.4.1
Vicious Incumbent Entry Game
198
9.5
Games with Non-Trivial Strategies
204
9.5.1
Setup for the model
205
9.5.2
Solving the Reformulated Model
209
9.5.3
Insights from Technology Development Problem
215
9.6
Software Solutions
216
viii
Contents
10
Data-Driven Causal Modeling
224
10.1
Causality versus Probability
225
10.1.1
Probability View
226
10.1.2
Causality View
227
10.2
Observational Indistinguishability
230
10.2.1
The Observational Indistinguishability Theorem
231
10.2.2
Causal Identification
235
10.3
Building Predictive Regression Models
241
10.3.1
From Structural Equation to Causal Models
241
10.3.2
Linear Regressions and Causal Models
242
10.3.3
Good Causal Models Imply Good Predictions
245
10.3.4
A Brief Note on Box Office Gross
248
Bibliography
255
Index
257
|
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| isbn | 9780415657594 9780415657600 |
| language | English |
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| publisher | Routledge |
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| spelling | Ryall, Michael J. Verfasser aut Inference and intervention Causal models for business analysis Michael D. Ryall; Aaron L. Bramson New York [u.a.] Routledge 2014 XIV, 261 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references and index Mathematisches Modell Decision making Mathematical models Decision making Statistical methods Business planning Statistical methods Entscheidungsprozess (DE-588)4121202-2 gnd rswk-swf Unternehmen (DE-588)4061963-1 gnd rswk-swf Mathematisches Modell (DE-588)4114528-8 gnd rswk-swf Unternehmen (DE-588)4061963-1 s Entscheidungsprozess (DE-588)4121202-2 s Mathematisches Modell (DE-588)4114528-8 s b DE-604 Bramson, Aaaron L. Verfasser aut Erscheint auch als Online-Ausgabe 978-0-203-07683-5 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026814668&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Ryall, Michael J. Bramson, Aaaron L. Inference and intervention Causal models for business analysis Mathematisches Modell Decision making Mathematical models Decision making Statistical methods Business planning Statistical methods Entscheidungsprozess (DE-588)4121202-2 gnd Unternehmen (DE-588)4061963-1 gnd Mathematisches Modell (DE-588)4114528-8 gnd |
| subject_GND | (DE-588)4121202-2 (DE-588)4061963-1 (DE-588)4114528-8 |
| title | Inference and intervention Causal models for business analysis |
| title_auth | Inference and intervention Causal models for business analysis |
| title_exact_search | Inference and intervention Causal models for business analysis |
| title_full | Inference and intervention Causal models for business analysis Michael D. Ryall; Aaron L. Bramson |
| title_fullStr | Inference and intervention Causal models for business analysis Michael D. Ryall; Aaron L. Bramson |
| title_full_unstemmed | Inference and intervention Causal models for business analysis Michael D. Ryall; Aaron L. Bramson |
| title_short | Inference and intervention |
| title_sort | inference and intervention causal models for business analysis |
| title_sub | Causal models for business analysis |
| topic | Mathematisches Modell Decision making Mathematical models Decision making Statistical methods Business planning Statistical methods Entscheidungsprozess (DE-588)4121202-2 gnd Unternehmen (DE-588)4061963-1 gnd Mathematisches Modell (DE-588)4114528-8 gnd |
| topic_facet | Mathematisches Modell Decision making Mathematical models Decision making Statistical methods Business planning Statistical methods Entscheidungsprozess Unternehmen |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026814668&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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