"Any student can learn the basic concepts of statistics if they are introduced as solutions to particular problems, and not formulas with a life of their own. In this text, students are introduced to a problem, asked to consider, conceptually, how one would address that problem, and then led through the derivation of the appropriate statistical formula. This applied method of teaching statistics through political science examples allows students to see the research method as problem solving. They learn the math, but only after they learn the concepts and methodological considerations that give the math context. The concepts throughout are presented through the lens of "observations and expectations," applied to myriad statistical techniques, both descriptive and inferential, as well as more generalized concepts of research methodology itself, such as hypothesis testing. Galderisi highlights that with each advance in technical sophistication, each statistical procedure is built on a small set of basic concepts, such as the reasons for standardization, the effects of outliers, or the concept of proportional reduction of error, to show that they are cumulative. More important than just memorizing a series of formula, this text emphasizes the underlying logic of statistical analysis for greater understanding. Further, the applications and examples drawn from political science (including law) allow students to better see how they can apply these concepts and techniques in their own research and in future coursework"--
In politics, you begin by asking theoretically interesting questions. Sometimes statistics can help answer those questions. When it comes to applied statistics, students shouldn’t just learn a vast array of formula—they need to learn the basic concepts of statistics as solutions to particular problems. Peter Galderisi demonstrates that statistics are a summary of how to answer the problem: learn the math but only after learning the concepts and methodological considerations that give it context.
With this as a starting point, Understanding Political Science Statistics asks students to consider how to address a research problem conceptually before being led to the appropriate formula. Throughout, Galderisi looks at problems through a lens of "observations and expectations," which can be applied to myriad statistical techniques, both descriptive and inferential. This approach links the answers researchers get from their individual data analysis to the research designs and questions from which these analyses are derived.
By emphasizing the underlying logic of statistical analysis for greater understanding and drawing on applications and examples from political science (including law), the book illustrates how students can apply statistical concepts and techniques in their own research, in future coursework, and simply as an informed consumer of numbers in public discourse.
The following features help students master the material:
Arvustused
The strength of this text is that Galderisi very carefully walks students through the statistical exercises and, in many cases, provides visual aids to help demonstrate the patterns or conclusions. He also works hard to take a step back from the statistics to help students understand the meaning of the analysis and why statistical conclusions may be invalid. This is not always included in many texts, which have more of a how-to approach, while the approach here is very thoughtful. Daniel Coffey, University of Akron
Understanding Political Science Statistics is an indispensable text that gives students the tools to understand how to think about and analyze political phenomenon. Galderisis applied, problem-focused approach to thinking about hypothesis testing and quantitative analysis ensure that it is both comprehensive and accessible to a broad range of readers with varying backgrounds and mathematical acumen. Vladimir Kogan, Ohio State University
Most textbooks in this field start with statistics, and then tack on political examples in aid of the math. The starting point for Peter Galderisis well-crafted new book is learning about politics, with the formulas and data always working to answer substantively important questions about the political world. Ive assigned it in my classes, and seen firsthand how engaged students become with the concepts and tools of quantitative analysis when a text piques and satisfies their curiosity about politics. Understanding Political Science Statistics does this, without sacrificing rigor in any way. Thad Kousser, UC San Diego
Understanding Political Science Statistics presents introductory statistics for political science students in an engaging, pragmatic, and problem-centric fashion that will be very approachable to undergraduates. Instead of an overly formal mathematical presentation, Galderisi explores research design and statistical concepts intuitively, showing students who may not be initially interested in the material how quantitative data and analysis can help them better understand contemporary issues in political science and public policy. Jack Reilly, New College of Florida
This is an ideal book for an undergraduate research methods course in political science. Galderisi offers a real treat for both students and instructors of statistics and research methods in political science. His work is thoroughly readable and at the same time provides a broad overview of the tools that everyone needs to know to be an informed consumerand potentially a future producerof quantitative research in political science. Mack Shelley, Iowa State University
1. Political Science, the Scientific Method, and Statistical Analysis:
An Overview
2. How Do We Measure and Observe?
3. Central Tendency as Summary Observation
4. Dispersion, Variation, Goodness of Fit as Summary Observation
5. Standardized Scores and Normal Distributions: The Concept of Relative
Observation
6. An Intuitive Introduction to Inference and Hypothesis Testing
7. Hypothesis Testing and the Concept of ASsociation: Observations and
Expectatiosn about the Difference between Two Means
8. Inferential Statistics for Proportions
9. Measuring Association for Nominal and Ordinal Data
10. Research Design and the Use of Control Variables
11. Different by How Much? Linear Regression
12. Retracing Our Steps: Hypotheses, Multiple Regression, and the EFfects of
Third Variables
Peter Galderisi has taught political science methods and statistics for more than three decades, and is currently a lecturer and local internship director in the Political Science Department at the University of California, San Diego. Previously, Galderisi was a Professor or Visiting Professor at Utah State, UCLA, UC Santa Cruz, and Cal State Fullerton. He specializes in U.S. political parties, campaigns and elections, American political development, interest groups, and election law.
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