ABSTRACT
The importance of data in environmental research has to do with two key objectives of the quantitative approach: quantifying relationships and testing hypotheses. Many environmental questions center on the relationship among variables. To perform quantitative analysis of data, it is important that the data be in a very specific format, which will be reflected in the structure of the database. All databases need to have the same structure in order to perform valid data analysis. This chapter explores part of a spreadsheet that contains information on per capita gross domestic product (PCGDP) and carbon dioxide (CO2) emissions for almost every country in the world in the year 2011. These data were taken from World Development Indicators, a database collected and maintained by the World Bank. The chapter considers the three types of random sampling: systematic, stratified, and cluster. All of these are designed to allow us to reproduce and understand what is going on in a population.
