Chapter 4 Exploratory Data analysis II: Descriptive Statistics, API Usage and Global Risk Analysis

Description

Use of Application Programming Interfaces (APIs) to build data pipelines. Explanations on obtaining descriptive statistics in R. Introduction to the use of APIs and introduction to the richness of unstructured data to inform empirical models in international business. In particular, we will use the EpiBibR package and the New York Times automatic programming interface to study the contribution of data sciences to the analysis of international risks, including pandemic risk and international political, cultural and economic responses.

Topics covered :

• 1 IPA

• 2 data pipelines

• 3 risk analysis and pandemic risk

Pre-Session Activities/Resources

• Hand, David. 2019. “What Is the Purpose of Statistical Modelling?”. Harvard Data Science Review 1 (1). https://doi.org/10.1162/99608f92.4a85af74.

• Warin, Thierry. 2020. "Global Research on Coronaviruses: An R Package. Journal of Medical Internet Research 22 (8): e19615. https://doi.org/10.2196/19615.

Session Activities/Resources

• Collecting international news data using data collection methods from websites such as the New York Times website: https://developer.nytimes.com/

• Using the https://github.com/warint/EpiBibR package

• Simulation “World Health Organization: Data Science for VIDOC Research-19”.

Post-Session Activities/Resources

• Lo, Andrew W., Kien Wei Siah, and Chi Heem Wong. 2019. “Machine Learning with Statistical Imputation for Predicting Drug Approvals.” Harvard Data Science Review 1 (1). https://doi.org/10.1162/99608f92.5c5f0525.

General Resources

• Galarnyk, Michael. 2019. “Understanding Boxplots.” Medium.

• Knaflic, Cole Nussbaumer. 2015. Storytelling with Data: A Data Visualization Guide for Business Professionals. Hoboken, New Jersey: Wiley.

• Lewinson, Eryk. 2019. “Violin Plots Explained.” Towards Data Science.

• ggplot2 pkgdown by Hadley Wickham et al.

• Data Visualization Cheat Sheet

• ggplot2 pkgdown by Hadley Wickham et al.

• Quantmod,Quantitative Financial Modelling & Trading Framework for R

how to search content in R across a number of websites: https://cran.r-project.org/web/packages/RWsearch/vignettes/RWsearch-4-Web-search-engines.html