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Instructor
Dr. Ruth Fisher, Instructor - Data Quality: Are Your Data Suitable For Answering Your Questions?

Dr. Ruth Fisher

Has a Ph.D in Economics from University of Chicago & a BA in Mathematics from University of Pennsylvania. She has over 25 years of experience in research and data analysis. Her experience span on theoretical, applied modeling and problem solving; Game Theory; Data Analytics; Behavioral Economics; and Systems Analysis.

Instructor: Dr. Ruth Fisher

  • Get a better understanding of context and limitations of data. Understand how well-suited data are for generating meaningful analyses.
  • Instructor has over 25 years of experience.
  • Instructor has a Ph.D from University of Chicago & a B.A from University of Pennsylvania.

Duration: 3h

Course Description

Data quality can make or break your analysis. Good techniques can't make up for bad data. This course will teach you how to assess the quality of your data and how well your data will serve to answer your questions.

What am I going to get from this course?

Get a better understanding of context and limitations of data. Understand how well-suited 
data are for generating meaningful analyses.

Prerequisites and Target Audience

What will students need to know or do before starting this course?

None required. Some experience working with data and some knowledge of statistics will be helpful.

Who should take this course? Who should not?

Anyone who works with data.

Curriculum

Module 1: Intro

Lecture 1 Intro
Lecture 2 Why Do We Need to Understand Data?
Lecture 3 Biggest Problems with Data
Lecture 4 Data Science Is Both Science and Art

Module 2: Creating a Roadmap for Your Analysis

Lecture 5 Why Do I Need an Analysis Roadmap?
Lecture 6 Creating an Analysis Roadmap, Part 1
Lecture 7 Creating an Analysis Roadmap, Part 2
Lecture 8 Exercise 1
Lecture 9 Exercise 1 - Explanation

Module 3: Understanding Your Data-Generating System, Part I

Lecture 10 Overview of Data Generating System
Lecture 11 Data Generating System - Content Provider
Lecture 12 Data Generating System - Data Collector
Lecture 13 Data Generating System - Customer
Lecture 14 Data Generating System - Client
Lecture 15 Exercise 2: Understanding Data Collector, Customer, Client
Lecture 16 Exercise 2 - Explanation: Understanding Data Collector, Customer, Client

Module 4: Understanding Your Data-Generating System, Part II

Lecture 17 Understanding Your Data-Generating System, Part II
Lecture 18 Context/Environment: The Situation
Lecture 19 Context/Environment: Choice Architecture
Lecture 20 Context/Environment: TED Talk Example
Lecture 21 Context/Environment: Summary/Conclusions
Lecture 22 Exercise 3: Understanding Context/Environment
Lecture 23 Exercise 3 - Explanation: Understanding Context/Environment

Module 5: Clearly Understanding Your Data

Lecture 24 Why Do I Need to Clearly Understand My Data?
Lecture 25 What Information Does Your Data Capture?
Lecture 26 What Do the Variables Look Like?
Lecture 27 Exercise 4: Understanding Your Data
Lecture 28 Exercise 4 - Explanation: Understanding Your Data

Module 6: Understanding Limitations of Your Data

Lecture 29 Why Do I Need to Understand Limitations of Data?
Lecture 30 Are the Data Biased?
Lecture 31 Are the Data Bad Proxies?
Lecture 32 Are the Data Inconsistent?
Lecture 33 Did Context/Environment Affect the Data?
Lecture 34 Exercise 5: Understanding Limitations of the Data
Lecture 35 Exercise 5 - Explanation: Understanding the Limitations of the Data

Module 7: Summary and Conclusions

Lecture 36 Summary
Lecture 37 Conclusions
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