1 - Introduction
from PART ONE - GETTING STARTED
Published online by Cambridge University Press: 15 September 2017
Summary
This book is based on class notes used to teach undergraduate and graduate students in political science and public policy how to prepare their data to conduct further analysis and provide recommendations to inform decision making. At both levels of education, I found students with different backgrounds in quantitative tools. That required me to develop a teaching approach to address the needs of students new to data analysis, so you should expect detailed explanations in this book.
My courses address different skills: from collecting, organizing, modeling, and analyzing the data, to visualizing and publishing it. This book focuses on data organization and collection and all their related procedures. This stage is arguably the most time-consuming and has been my main concern over the years. In general, books for quantitative analysis devote most of their pages to teaching quantitative concepts while sharing data that has already been well organized into a table readable by most software (Stata, SPSS, SAS, etc), or into a simple comma-separated values (CSV) file to be used by any software. However, every scholar (student, researcher, or professor) or professional will need to prepare a particular data set for his or her current needs. It is then that they may experience a hard time. The literature lacks material on preparing data sets for students in the social sciences, so it has been my goal to provide those competences in basic data organization.
When I embarked on teaching this stage to students, I discovered there is no simple, right, or unique way of doing it. In this book, I simply share my way of teaching it, not how it should necessarily be done. This is a potential challenge or weakness of this book because I do not present a formal paradigm for data organization. Nevertheless, I share strategies that have proven to be helpful for students who lack a quantitative or computational background.
My target audience might be familiar with particular software, but may never have used it to collect or clean data or to automate those processes. There is no function in an SPSS/Stata/Excel window menu that says either collecting or cleaning the data. Collecting, cleaning, and formatting data require the flexibility that programming languages provide, which motivated me to teach some coding skills to my students.
- Type
- Chapter
- Information
- Introduction to Data Science for Social and Policy ResearchCollecting and Organizing Data with R and Python, pp. 3 - 11Publisher: Cambridge University PressPrint publication year: 2017