This practical text provides students with the statistical tools needed to analyze data, and shows how statistics can be used as a tool in making informed, intelligent policy decisions. The authors' approach helps students learn what statistical measures mean and focus on interpreting results, as opposed to memorizing and applying dozens of statistical formulae. The book includes more than 500 end-of-chapter problems, solvable with the easy-to-use Excel spreadsheet application developed by the authors. This template allows students to enter numbers into the appropriate sheet, sit back, and analyze the data. This comprehensive, hands-on textbook requires only a background in high school algebra and has been thoroughly classroom-tested in both undergraduate and graduate level courses. No prior expertise with Excel is required. A disk with the Excel template and the data sets is included with the book, and solutions to the end-of-chapter problems will be provided on the M.E. Sharpe website.

CD-ROM included contains Polystat and sample data sets.

As the first book ever published for public administration statistics courses, APPLIED STATISTICS FOR PUBLIC AND NONPROFIT ADMINISTRATION, International Edition makes a difficult subject accessible to students and practitioners of public administration who have little background in statistics or research methods. Steeped in experience and practice, this landmark text remains the first and best in research methods and statistics for students and practitioners in public--and nonprofit--administration. All statistical techniques used by public administration professionals are covered, and all examples in the text relate to public administration and the nonprofit sector. The text avoids jargon and formulae; instead, it uses a step-by-step approach that facilitates student learning.

For graduate students in the social and health sciences, featuring essential concepts and equations most often needed in scholarly publications. Uses excerpts from the scholarly literature in these fields to introduce new concepts. Uses publicly-available data that are regularly used in social and health science publications to introduce Stata code and illustrate concepts and interpretation. Thoroughly integrates the teaching of statistical theory with teaching data processing and analysis. Offers guidance about planning projects and organizing code for reproducibility Shows how to recognize critiques of the constructions, terminology, and interpretations of statistics. New edition focuses on Stata, with code integrated into the chapters (rather than appendices, as in the first edition) includes Stata’s factor variables and margins commands and Long and Freese’s (2014) spost13 commands, to simplify programming and facilitate interpretation.

Instructs readers on how to use methods of statistics and experimental design with R software Applied statistics covers both the theory and the application of modern statistical and mathematical modelling techniques to applied problems in industry, public services, commerce, and research. It proceeds from a strong theoretical background, but it is practically oriented to develop one's ability to tackle new and non-standard problems confidently. Taking a practical approach to applied statistics, this user-friendly guide teaches readers how to use methods of statistics and experimental design without going deep into the theory. Applied Statistics: Theory and Problem Solutions with R includes chapters that cover R package sampling procedures, analysis of variance, point estimation, and more. It follows on the heels of Rasch and Schott's Mathematical Statistics via that book's theoretical background—taking the lessons learned from there to another level with this book’s addition of instructions on how to employ the methods using R. But there are two important chapters not mentioned in the theoretical back ground as Generalised Linear Models and Spatial Statistics. Offers a practical over theoretical approach to the subject of applied statistics Provides a pre-experimental as well as post-experimental approach to applied statistics Features classroom tested material Applicable to a wide range of people working in experimental design and all empirical sciences Includes 300 different procedures with R and examples with R-programs for the analysis and for determining minimal experimental sizes Applied Statistics: Theory and Problem Solutions with R will appeal to experimenters, statisticians, mathematicians, and all scientists using statistical procedures in the natural sciences, medicine, and psychology amongst others.

Accessibly written and easy to use, Applied Statistics Using SPSS is an all-in-one self-study guide to SPSS and do-it-yourself guide to statistics. Based around the needs of undergraduate students embarking on their own research project, the text′s self-help style is designed to boost the skills and confidence of those that will need to use SPSS in the course of doing their research project. The book is pedagogically well developed and contains many screen dumps and exercises, glossary terms and worked examples. Divided into two parts, Applied Statistics Using SPSS covers : 1. A self-study guide for learning how to use SPSS. 2. A reference guide for selecting the appropriate statistical technique and a stepwise do-it-yourself guide for analysing data and interpreting the results. 3. Readers of the book can download the SPSS data file that is used for most of the examples throughout the book. Geared explicitly for undergraduate needs, this is an easy to follow SPSS book that should provide a step-by-step guide to research design and data analysis using SPSS.

While mapped data provide a common ground for discussions between the public, the media, regulatory agencies, and public health researchers, the analysis of spatially referenced data has experienced a phenomenal growth over the last two decades, thanks in part to the development of geographical information systems (GISs). This is the first thorough overview to integrate spatial statistics with data management and the display capabilities of GIS. It describes methods for assessing the likelihood of observed patterns and quantifying the link between exposures and outcomes in spatially correlated data. This introductory text is designed to serve as both an introduction for the novice and a reference for practitioners in the field Requires only minimal background in public health and only some knowledge of statistics through multiple regression Touches upon some advanced topics, such as random effects, hierarchical models and spatial point processes, but does not require prior exposure Includes lavish use of figures/illustrations throughout the volume as well as analyses of several data sets (in the form of "data breaks") Exercises based on data analyses reinforce concepts

Research Methods and Statistics for Public and Nonprofit Administrators: A Practical Guide is a comprehensive, easy-to-read, core text that thoroughly prepares readers to apply research methods and data analysis to the professional environments of public and non-profit administration. The authors expertly incorporate original case examples to demonstrate concepts using “real actors,” facing specific scenarios, in which research methods must be applied. This unique approach—presented in language accessible to both students new to research as well as current practitioners—guides the reader in fully understanding the research options detailed throughout the text.

A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.