Modules Overview

A module, in the context of this book, is a self-contained unit of study that focuses on specific concepts, tools, or applications in economic data analysis. These modules serve as building blocks, each progressively introducing you to more complex or varied facets of the subject matter. In this section, we’ll outline a series of modules tailored to provide both foundational knowledge and advanced insights, ensuring a comprehensive understanding of economic data analysis.

The book is divided into six main parts, which are further broken down into the following modules:

• Part I: Introduction to R
  • Module A: Introduction to R
• Part II: Measurement in Economics
  • Module B: Financial Performance Indicators
  • Module C: Macro Indicators
  • Module D: Financial Market Indicators
• Part III: Economic Data Processing
  • Module E: Economic Data Processing
• Part IV: Patterns in Economics
  • Module F: Temporal Patterns in Economics
  • Module G: Regional Patterns in Economics
• Part V: Insights From Real-Time Data and Surveys
  • Module H: Insights From Consumer Surveys
  • Module I: Insights From Real-Time Data
  • Module J: Insights From Forecaster Data
• Part VI: Insights From Textual Data
  • Module K: Insights From Google Trends
  • Module L: Insights From Newspapers
  • Module M: Insights From Social Media

Within each module, you’ll find (a) reading assignments from the Economic Data Analysis textbook, (b) associated courses from DataCamp, and (c) detailed instructions on drafting a data report that addresses the module’s subject matter. The following sections detail these three module components:

1. Textbook Engagement
2. Learn R with DataCamp
3. Data Report Instructions