W201 RDADA
Welcome!
Calendar
Onboarding
Purchases
Accounts
CalNet ID
bConnected
I School Intranet
Slack
Questionnaire
Assignments
Skills
Group 1
Individual 1
Participation 1
Group 2
Individual 2
Participation 2
Individual 3
Group 3
Final
Final
Weekly Units
Prologue
1 Data Science: More Than a Technical Discipline
Readings
Davenport (
2006
)
↑
EMC (
2011
)
↑
LaValle et al. (
2011
)
↑
Le Grand and Cooper (
2012
)
↑
Martin (
2010
)
↑
Salsburg (
2002
)
↑
Shan et al. (
2015
)
↑
Weathington (
2018
)
↑
Lectures
1.1 Introduction to the Week
↑
1.3.1 Let’s Talk “Big Data”
↑
1.3.2
↑
1.3.4
↑
1.3.5
↑
1.3.7
↑
1.3.11
↑
1.3.13
↑
1.4.1 What does Data Science Mean to the World?
↑
1.4.2
↑
1.5.1 What Does Data Science Mean for This Class?
↑
1.5.2
↑
1.5.3
↑
1.5.4
↑
1.6 An Information School Perspective on IT and Data Science
↑
1.7.1 Problem Types
↑
1.7.2
↑
1.7.3
↑
1.8.1 Data and the Top Decision Maker
↑
1.8.2
↑
1.8.3
↑
1.8.4
↑
1.9 Sum-Up of Week 1
↑
Assignments Due
Perform
Compose
Review
Some notes on pedagogy
Act I: Decision Making
2 When Big Data Meets Big Decision
Readings
Alamar and Mehrotra (
2011
)
↑
Loveman (
2003
)
↑
Shah, Horne, and Capellá (
2012
)
↑
Voytek (
2012
)
↑
Lectures
2.1 Introduction to the Week
↑
2.3.1 From Business Intelligence to Data Science
↑
2.3.2
↑
2.3.3
↑
2.3.4
↑
2.3.5
↑
2.3.6
↑
2.3.7
↑
2.4.1 A Perspective From IBM’s Journey
↑
2.4.2
↑
2.4.3
↑
2.4.4
↑
2.4.5
↑
2.5 Summary and Wrap-Up
↑
Assignments Due
Perform
Compose
Review
3 High-Pressure Decision Making: People and Organization
Readings
Allison and Zelikow (
1999
a
)
↑
Allison and Zelikow (
1999
b
)
↑
Neustadt and May (
1988
)
↑
Lectures
3.1 Introduction to High-Pressure Decision Making
↑
3.2 Video Clip of Cuban Missile Crisis
↑
3.4 History of the Cuban Missile Crisis
↑
3.4.1 “We’ve Been Fooled…”
↑
3.5 Crisis Decision Making I
↑
3.5.1 Crisis Decision Making II
↑
3.6 Decision-Making Models
↑
3.7.1 Cuban Missile Crisis Decision Discussion
↑
3.7.2
↑
3.7.3
↑
3.7.4
↑
3.7.5
↑
3.7.6
↑
3.7.7
↑
3.7.1 Public Policy Perspective I: Michael Nacht
↑
3.7.2 Public Policy Perspective II: Craig Denny
↑
3.8 Introduction to Vietnam War and Body Count Model
↑
3.9 Analyzing Vietnam War and Body Count Model
↑
3.9.1.1 Vietnam vs. War on Terrorism vs. Cyber
↑
3.9.1.2
↑
3.9.1.3
↑
3.9.1.4
↑
3.9.1.5
↑
3.9.1.6
↑
3.9.1.7
↑
3.10 Week 3 Wrap-Up
↑
Assignments Due
Perform
Compose
Review
4 Biases in Decision Making
Readings
Davenport (
2009
)
↑
Hammond, Keeney, and Raiffa (
1998
)
↑
Kahneman (
2013
b
)
↑
Kahneman (
2013
a
)
↑
Stauffer (
2002
)
↑
Lectures
4.1 Introduction to Biases
↑
4.3.0.1 Biases Can Be Fun
↑
4.3.0.2
↑
4.3.0.3
↑
4.3.1 Deadly Serious Stuff I
↑
4.3.2 Deadly Serious Stuff II
↑
4.4 Common Biases Overview
↑
4.4.1.1 Biases Example
↑
4.4.1.2
↑
4.4.1.3
↑
4.4.1.4
↑
4.4.1.5
↑
4.4.1.6
↑
4.4.1.7
↑
4.5 Makes Choices Based on Interests
↑
4.6 Bias Interview
↑
4.7 Difference in Kind vs. Difference in Degree
↑
4.8 Week 4 Wrap-Up
↑
Assignments Due
Perform
Compose
Review
5 What Is Knowing?
Readings
Anderson (
2008
)
↑
Burton (
2008
)
↑
Centola and Baronchelli (
2015
)
↑
Kuhn (
1962
)
↑
Lectures
5.1 Introduction to What is Knowing?
↑
5.3 What Does It Mean to Know? Part I
↑
5.3.1 What Does It Mean to Know? Part II
↑
5.4 The “Scientific Method”
↑
5.4.1 The Real Scientific Method
↑
5.4.2 Tests and Data in Health Care: Michael Wollin
↑
5.5 Sports Strategy
↑
5.5.1 Deception in Sports
↑
5.5.2.1 Your Own Data Deception
↑
5.5.2.2
↑
5.5.2.3
↑
5.5.2.4
↑
5.5.2.5
↑
5.5.2.6
↑
5.5.2.7
↑
5.5.2.8
↑
5.5.2.9
↑
5.6 Defining Certainty
↑
5.6.1 How Experts View Certainty: Craig Denny
↑
5.6.2 ACH Instructions
↑
5.7 The Demand for “Certainty”
↑
5.8 Practical Value of the Scientific Method
↑
5.8.1 Scientific Method Examples
↑
5.8.2 Popper and Kuhn
↑
5.9 Fewer and Better Disagreements
↑
5.9.1 Fewer and Better Disagreements Examples: Baruch Fischoff
↑
5.10 Week 5 Wrap-Up
↑
Assignments Due
Perform
Compose
Review
Live Session Agenda
2 Main Meeting:
Anderson (
2008
)
&
Centola and Baronchelli (
2015
)
3 Breakouts:
Burton (
2008
)
&
Kuhn (
1962
)
Implications
Act II: Research Design
6 Practical Research Design for Real People
Readings
Creswell (
2009
a
)
↑
Creswell (
2009
b
)
↑
Kramer, Guillory, and Hancock (
2014
)
↑
Panger (
2014
)
↑
Lectures
6.1 Introduction to Questioning
↑
6.2 Weekly Video
↑
6.4 Importance of Good Research Design
↑
6.4.1 Induction vs. Deduction
↑
6.4.2 Linear Model of Research Design
↑
6.4.3 How Do We Sell a Slide Projector?
↑
6.4.4 Alvarez Story of the Meteor
↑
6.4.5 Iterative Research
↑
6.5 Qualitative Data
↑
6.6 Design Thinking in Practice
↑
6.6.1 IDEO Shopping Cart
↑
6.6.2 A Consultant’s View
↑
6.7 Design Thinking Is Asking the Right Questions
↑
6.7.1 Ask Them!
↑
6.7.2 Asking Better Questions
↑
6.7.3.1 Common Questions Aren’t the Best
↑
6.7.3.2
↑
6.7.3.3
↑
6.7.3.4
↑
6.7.3.5
↑
6.8 Expert Mind vs. Beginner Mind
↑
6.9 Accumulated Wisdom
↑
6.10 Elegant Questions Are an Art Form
↑
6.10.1 Beautiful Questions
↑
6.11 Week 6 Wrap-Up
↑
Assignments Due
Perform
Compose
Slug Debug
Review
Live Session Agenda
1. Lobby: Warm-up
2.
Kramer, Guillory, and Hancock (
2014
)
3.
Panger (
2014
)
4. Group Consultations: Private Memos
7 Good Logic, Bad Logic, and Everything in Between
Readings
Creswell (
2009
c
)
↑
Creswell (
2009
d
)
↑
Ward, Clack, and Haig (
2016
)
↑
Lectures
7.1 Introduction to Fallacies, Assumptions, and Conventions
↑
7.3 DEAD Conventions
↑
7.4 Similarities Are More Interesting Than Differences
↑
7.5 Introduction to Demonstrating Fallacies
↑
7.6.0.1 Demonstrating Fallacies
↑
7.6.0.2
↑
7.6.0.4
↑
7.6.0.5
↑
7.6.0.7
↑
7.6.1 Other Fallacies
↑
7.6.2 Bad Decisions Are Human
↑
7.7 IBM Internet of Things
↑
7.8 Rules of Inference
↑
7.9 Example of Rules of Inference
↑
7.9.1 Two Limits of Inferential Rules
↑
7.10 Week 7 Wrap-Up
↑
7.11 Video
↑
Assignments Due
Perform
Public statement
Submission Instructions
Compose
Review
8 Research Design Case Study
Readings
Gitlin (
1985
a
)
↑
Gitlin (
1985
b
)
↑
Gitlin (
1985
c
)
↑
Gitlin (
1985
d
)
↑
Lund (
2014
)
↑
Lectures
8.1 Introduction to Research Design Case Study Intro
↑
8.3 Case Study 1: Using Data to Disrupt a Media Model
↑
8.4 Case Study 2: Improving Relationships in Health Care
↑
8.5 Case Study 3: Gambling on Data Insights
↑
8.6 Case Study 4: Fitting the Numbers
↑
8.7 Case Study 5: Insuring through Data
↑
8.8 Video
↑
Assignments Due
Perform
Compose
Review
Week 8 Live Session Agenda
Breakouts: Literature Review Discussion Questions
9 Storytelling through Words and Pictures
Readings
Huff (
1954
a
)
↑
Huff (
1954
c
)
↑
Huff (
1954
d
)
↑
Huff (
1954
e
)
↑
Lectures
9.1 Introduction to the Week
↑
9.2 Conveying Findings
↑
9.3 Telling a Good Story
↑
9.4 Insights From Pixar
↑
9.5 Wrap-Up
↑
Assignments Due
Perform
Compose
Review
Act III: Conveying Findings
10 How Visualizations Work
Readings
Huff (
1954
f
)
↑
Huff (
1954
g
)
↑
Offenhuber (
2010
)
↑
Perkel (
2018
)
↑
Edward R Tufte (
2009
a
)
↑
Edward R Tufte (
2009
b
)
↑
Lectures
10.1 Introduction to How Visualizations Work
↑
10.2 Weekly Video
↑
10.3 Assigned Readings
↑
10.4 Information Visualization 101
↑
10.4.1 Information Visualization Examples
↑
10.4.2 Expert Opinion
↑
10.5 Visualizations Through History
↑
10.6 Visualization Discussion
↑
10.7 Week 10 Wrap-Up
↑
Assignments Due
Perform
Compose
Review
11 Persuasion in Business and Real Life
Readings
Huff (
1954
h
)
↑
Huff (
1954
i
)
↑
Huff (
1954
j
)
↑
Huff (
1954
b
)
↑
Kleiner and Roth (
1997
)
↑
Laurila (
2012
)
↑
Williams (
1991
)
↑
Lectures
11.1 Introduction to Persuasion
↑
11.2 How Maps Persuade
↑
11.3 Behavioral Economics Is About Persuading… Ourselves
↑
11.4 Experts in Persuasion
↑
11.5 A Model of “Other” People
↑
11.6 When Persuasion Goes Wrong . . . and Right
↑
11.7 Wrap-Up
↑
Assignments Due
Perform
a.k.a.
Excavating Story Structure
Selection
Analysis
12 Data Science Futures
Readings
Duhigg (
2012
)
↑
Hawkins (
2018
)
↑
Joy (
2000
)
↑
Rosenberg, Confessore, and Cadwalladr (
2018
)
↑
Lectures
12.1 Introduction to Ethics and Privacy
↑
12.2 Weekly Video
↑
12.3 Assigned Readings
↑
12.4 Law vs. Ethics
↑
12.5 Experiences and Concerns Around Data
↑
12.5.1 Watson and the Department of Defense
↑
12.5.2 The Bill Joy Argument
↑
12.6 Minority Report
↑
12.7 Vectors of Data Science
↑
12.8 Why Companies Imagine Futures
↑
12.9 A View From Herman Miller
↑
12.10 Week 12 Wrap-Up
↑
Assignments Due
Compose
The Original Final Prompt
Your Revised Final Prompt
13 Consultation Week
Readings
Lectures
Assignments Due
Perform
Compose
Review
Epilogue
14 Finals Week
End of Term Survey (2U)
Course Evaluation (UC)
Starter Prompt
Readings
Lectures
Assignments Due
Perform
Compose
Review
Resources
Office Hours
GitHub Workflows
Basic Submission
Squash Merge
DSM Template
Act I
Decision Making
Act II
Research Design
Data Replicability
Organizational Design
Act III
Communicating Findings
Scope
Pre-recording
Citation Management
Zotero
Citekeys
Better BibTex
Portfolio Deployment
Step 1: Get compute
Features of your Binder Pod
Step 2: Update your repo
Step 3: Hack away!
Step 4: Build Rmd into HTML
Step 5: Deploy to w201rdada.github.io
Step 6: Activate GitHub Pages
Step 7: Bask in your glory!
Docker Deploy (Deprecated)
Individual Assignment 3.1: Polish and Publish Big Ideas #1 & #2
Walkthroughs
Step 1: Expect
errors
!
Step 2: Install Docker
Step 3: Update Your Portfolio
Step 4: Launch RStudio Server Container
Step 5: Build HTML from Rmarkdown
Step 6: Deploy to w201rdada.github.io
Step 7: Activate GitHub Pages
Step 8: Kick back and bask in your glory!
Submission Instructions
Seasons
End of Winter
Spring
Summer
Fall
Beginning of Winter
Bibliography
ISVC
Question!
Comment!
Discuss!
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W201 Research Design and Applications for Data Analysis (RDADA)
Squash Merge
Figure 38: Squashing Commits from Branch to Master