Chapters Overview
Chapter 01: Origins of Data
Chapter summary: This chapter is about data collection and data quality.
This chapter starts by introducing key concepts of data. It then describes the most important methods of data collection used in business, economics, and policy analysis, such as web scraping, using administrative sources, and conducting surveys. We introduce aspects of data quality, such as validity and reliability of variables and coverage of observations. We discuss how to assess and link data quality to how the data was collected. We devote a section to Big Data to understand what it is and how it may differ from more traditional data. This chapter also covers sampling, including random sampling and potential biases due to noncoverage and nonresponse, as well as ethical issues and some good practices in data collection.
Case Studies:
Finding a good deal among hotels
Comparing online and offline prices
Slides:
Chapter 01 Slideshow
Chapter 02: Preparing Data for Analysis
Chapter summary: This chapter is about preparing data for analysis: how to start working with data.
First, we clarify some concepts: types of variables, types of observations, data tables, and datasets. We then turn to the concept of tidy data: data tables with the same kinds of observations. We discuss potential issues with observations and variables, and how to deal with those issues. We describe good practices for the process of data cleaning and discuss the additional challenges of working with Big Data.
Case Studies:
CH02A Finding a good deal among hotels: data preparation
CH02B Finding a good deal among hotels: data preparation
Slides:
Chapter 02 Slideshow
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