Statistics and Data Analysis for Social Science helps students to build a strong foundational understanding of statistics by providing clarity around when and why statistics useful. Rather than focusing on the “how to” of statistics, author Eric J. Krieg simplifies the complexity of statistical calculations by introducing only what is necessary to understanding each concept. Every chapter is written around and applied to a different social problem or issues—enabling students to broaden their imagination about the statistical “tools” that can be used to make sense of our world and, maybe, to make the world a better place.
This text helps build students' confidence and ability in doing statistical analysis, by slowly moving from concepts that require little computational work to those that require more.
Using plain language and assuming no prior knowledge of statistics and coding, the book provides a step-by-step guide to analyzing real-world data with the statistical program R for the purpose of answering a wide range of substantive ...
... on Behavioral and Social Sciences and Education, Committee on Basic Research in the Behavioral and Social Sciences. http://www.nap.edu/catalog/992.html BEHAVIOR, MIND, AND BRAIN 28 apparently learned well, at least to the extent of ...
The book provides practical guidance on combining methods and tools from computer science, statistics, and social science.
Statistics for Social Data Analysis
They include Jill Dolan, Chris Eisgruber, Dave Lee, Nolan McCarty, Debbie Prentice, and Val Smith. ... I also thank Neal Beck, Andy Hall, Ryan Moore, and Marc Ratkovic for their comments on earlier versions of the manuscript.
Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how to use R to manage, visualize, and ...
New to the 2nd edition of Statistics for the Social Sciences, is the author's explanation and teaching on how to do analysis using SAS and SPSS and how to interpret the resultant computer-generated output.
With updates in every chapter, this edition expands its topics to include regression analysis, con
Englewood Cliffs: Prentice-Hall. Lee, M. D. (2001). Determining the dimensionality of multidimensional scaling representations for cognitive modeling. Journal of Mathematical Psychology, 45, l49—l66. Lee, M. D., & Pope, K. J. (2003).