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Professors Kellstedt and Whitten present an integrated approach to research design and empirical analyses in which researchers can develop and test causal theories. The authors use examples from political science research that students will find interesting and inspiring, and that will help them understand key concepts. The book makes technical material accessible to students who might otherwise be intimidated by mathematical examples.

This revised second edition refines discussions from the first edition, with a new chapter on how to write an original research project. The second edition also contains an additional forty exercises and adds definitions for terms discussed in each chapter. Mostly Harmless Econometrics. Joshua D. Applying Social Statistics. Jay Alan Weinstein. Designing Social Inquiry. Gary King. Coherent Stress Testing. Riccardo Rebonato. Razia Azen.

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John Fox. The Essentials of Political Analysis. Philip H. Handbook of Econometrics. James J. Statistical Models. David A. Agent-based Models. Domenico Delli Gatti. Political Science Research Methods. Jason D. Statistical Modelling for Social Researchers. Roger Tarling. Applied Regression. Colin Lewis-Beck. Political Complexity. Diana Eva-Ann Richards. Statistics for the Behavioural Sciences. Riccardo Russo. Understanding and Applying Research Design. Martin Lee Abbott. Statistics for Research. George Argyrous. Research Method in Management. Rittik Chandra. Statistical Modeling and Inference for Social Science.

Sean Gailmard. Working with Political Science Research Methods. Natural Experiments in the Social Sciences. Thad Dunning. Cal Clark. Spatial Analysis for the Social Sciences. David Darmofal. Cindy Kam. The Craft of Political Research.


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Hypotheses in Political Science Research

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Kellstedt and Guy D. We then introduce the goals and standards of political science research that will be our rules of the road to keep in mind throughout this book. The chapter concludes with a brief overview of the structure of this book. Doubt is the beginning, not the end, of wisdom.

We aim to make the common technical language of political science accessible to you. We want you to be better able to evaluate such claims critically. This is obviously the most ambitious of our goals. In our teaching we often have found that once skeptical students get comfortable with the basic tools of political science, their skepticism turns into curiosity and enthusiasm.

Under this alternative way, for example, a course offered in on the politics of the European Union EU would have taught students that there were 15 member nations who participated in governing the EU through a particular set of institutional arrangements that had a particular set of rules. An obvious problem with this alternative way is that courses in which lists of facts are the only material would prob- ably be pretty boring. An even bigger problem, though, is that the political world is constantly changing. In the EU is made up of 27 member nations and has some new governing institutions and rules that are different from what they were in By contrast, a theoretical approach to politics helps us to better understand why changes have come about and their likely impact on EU politics.

Whitten Excerpt More information 3 1. A key part of this process is thinking about the world in terms of models in which the concepts of interest become variables1 that are causally linked together by theories. We conclude this chapter with a brief overview of the structure of this book. Scientists are lumped into different disciplines that develop standards for evaluating evidence. This is certainly true of the way that political scientists approach politics.

Fundamentals of Political Science Research

So what do political scientists do and what makes them scientists? A basic answer to this question is that, like other scientists, political scientists develop and test theories. A theory is a tentative conjecture about the causes of some phenomenon of interest. Once a theory has been developed, we can restate it into one or more testable hypotheses. A hypothesis is a theory-based statement about a relationship that we expect to observe. For every hypothesis there is a corresponding null hypothesis. A null hypothesis is also a theory-based statement but it is about what we would expect to observe if our theory was incorrect.

Hypothesis testing is a process in which scientists evaluate systematically collected evidence to make a judgement of 1 When we introduce an important new term in this book, that term appears in boldface type. We discuss variables at great length later in this and other chapters. Figure 1. We then derive one or more hypotheses about what our the- Evaluation of causal theory ory leads us to expect when we measure our concepts of interest which we call variables — as subsequently discussed in the real world.

In the third step, we conduct empirical tests of Scientific knowledge our hypotheses. Next, from the results of our hypothesis tests, we evaluate our causal theory. On hearing of a new theory, other scientists will challenge this theory and devise further tests. It is important to underscore here the nature of the testing that scientists carry out. One way of explaining this is to say that scientists are not like lawyers in the way that they approach evidence.

We show more of the complexity of this approach in later chapters. Whitten Excerpt More information 5 1. When faced with evidence that supports their case, lawyers try to emphasize the applicability of the supportive evidence. At the beginning of a trial, lawyers develop a strategy to prove their case. In contrast, at the beginning of a research project, scientists will think long and hard about the most rigorous tests that they can conduct.

As scientists evaluate systematically collected evidence to make a judgment of whether the evidence favors their hypothesis or favors the corresponding null hypothesis, they always favor the null hypothesis. Statistical techniques allow scientists to make probability-based statements about the empirical evidence that they have collected. You might think that, if the evidence was 50—50 between their hypothesis and the corresponding null hypothesis, the scientists would tend to give the nod to the hypothesis from their theory over the null hypothesis.


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In practice, though, this is not the case. Even when the hypothesis has an 80—20 edge over the null hypothesis, most scientists will still favor the null hypothesis. Because scientists are very worried about the possibility of falsely rejecting the null hypothesis and therefore making claims that others ultimately will show to be wrong. Together, these shared assumptions and accepted theories form what we call a paradigm. This state of research under an accepted paradigm is referred to as normal science.

This was an assumption that had informed theories about planetary movement for thousands of years.