Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the[...]
Students in the sciences, economics, psychology, social sciences, and medicine take introductory statistics. Statistics is increasingly offered at the high school level as well. However, statistics can be notoriously difficult to teach as it is seen by many students as difficult and boring, if not [...]
On the night of the 2000 presidential election, Americans watched on television as polling results divided the nation's map into red and blue states. Since then the color divide has become symbolic of a culture war that thrives on stereotypes--pickup-driving red-state Republicans who vote based on G[...]
Incorporating new and updated information, this second edition of THE bestselling text in Bayesian data analysis continues to emphasize practice over theory, describing how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Its world-class authors provide guida[...]
Social scientists become experts in their own disciplines but aren't always familiar with what is going on in neighboring fields. To foster a deeper understanding of the interconnection of the social sciences, economists should know where historical data come from, sociologists should know how to th[...]