Summary
Contents
Subject index
A step-by-step guide to writing empirically-focused research papers. Powner, an expert teacher, offers clear, detailed, and often entertaining instructions for formulating hypothesis, doing pre-research, selecting appropriate research designs, selecting cases, collecting and managing both qualitative and quantitative data, preparing data for analysis, writing up research findings, practicing peer review, and delivering findings in posters and presentations, and preparing work for publication. Each chapter contains interesting and useful examples (both hypothetical and real), exercises to help students apply what they've learned, and pedagogical features to inspire, instructor, and aid further research, including “Peer Pointers” (quotes from former students that illustrate “aha!” moments), “Talking Tips” (fundamental and surprising tip for research), and appendix materials that include formatting guidelines and a list of major data sources for political science. Making the book as turnkey as possible are downloadable student and instructor resources, including lesson plans and activities for instructors, solutions manual to in-text exercises, links to common citation guides, data sources, journals that publish student papers, and conferences where students can share papers and posters.
Preparing Quantitative Data for Analysis
Preparing Quantitative Data for Analysis
In this chapter, we move into the technical parts of paper writing: where you get your data into the statistics program and prepare to do something with them. This chapter includes a combination of very practical information about getting your data into the program and preparing them for analysis, and also pre-analysis steps you should take such as identifying and dealing with data irregularities and potential statistical problems. We begin with getting your data into the stats program, cleaning them so that they are ready for trustworthy analysis, and identifying and correcting any highly problematic aspects of the data. We then consider other ways to manipulate data, such as creating interaction terms, scales, and indices. Finally, we identify ...
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