Inferential Statistics and Complex Surveys
Welcome to Inferential Statistics and Complex Surveys.This is a course about making inferences with surveys. What does it mean to make an inference? The simplest way to put it is saying that we will use things we know (data) to learn about things we do not know (parameters).
This course aims:
- To introduce students to the estimation and statistical inference with survey data from complex sampling designs
- To foster data analysis skills with real-world survey data based on complex sampling designs.
The objective of these materials is not to replace the readings, but to provide a more concise and, especially, applied summary of the course contents. Part I is about getting the tools ready for the course (R and RStudio) and learning their basics. Part II presents a general overview of the main concepts related to making statistical inferences with complex surveys. Then, Part III develops the sampling strategies that conform the complex sampling designs commonly used in real world surveys. Finally, Part IV introduces different ways of doing statistical inference and presenting its results with applied examples from the European Social Survey.
These course materials are a work in progress. Parts I and II are ready, the rest of the chapters will be completed during this semester before the relevant sessions on the topics take place.
Feedback and comments regarding this document are welcome, please contact me at firstname.lastname@example.org.
These materials have been prepared with the help of many resources. Especially, I would like to highlight the content provided in STAT 545 for the practical issues of installing and using software (for now Part I comes mostly from it with minor changes), as well as a fundamental reference for creating these course materials. Also, the course Quantitative Social Science Methods I by Prof. King has been useful in the developing explanations of data generation processes and statistical inferences. Moreover, all the resources made available by R (R Core Team 2020) and its community have been fundamental. In particular, the tidyverse (Wickham et al. 2019) and survey (Lumley 2020) packages are central in this course. Finally, these materials are possible thanks to the bookdown package (Xie 2020).
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