Fundamental Statistics for the Behavioral Sciences
FUNDAMENTAL STATISTICS FOR THE BEHAVIORAL SCIENCES focuses on providing the context of statistics in behavioral research, while emphasizing the importance of looking at data before jumping into a test.
This book is the revised and extended second edition of Statistics for Linguistics with R. The comprehensive revision includes new small sections on programming topics that facilitate statistical analysis, the addition of a variety of statistical functions readers can apply to their own data, and a revision of overview sections on statistical tests and regression modeling. The main revision is a complete rewrite of the chapter on multifactorial approaches, which now contains sections on linear regression, binary and ordinal logistic regression, multinomial and Poisson regression, and repeated-measures ANOVA.
Master the fundamentals of discrete mathematics and proof-writing with MATHEMATICS: A DISCRETE INTRODUCTION! With a clear presentation, the mathematics text teaches you not only how to write proofs, but how to think clearly and present cases logically beyond this course. Though it is presented from a mathematician's perspective, you will learn the importance of discrete mathematics in the fields of computer science, engineering, probability, statistics, operations research, and other areas of applied mathematics. Tools such hints and proof templates prepare you to succeed in this course.
Illustrated Glossary for Transport Statisics, 4th Edition
The present fourth edition is the result of continuing valuable cooperation between three organisations (Eurostat, UNECE and ITF), that - through the action of the Intersecretariat Working Group (IWG Trans.) - have put a sustained effort into meeting the need to harmonise transport statistics at the international level. The Glossary now comprises 735 definitions and represents a point of reference for all those involved in transport statistics. By following the guidance contained within these definitions, a considerable contribution will be given to the improvement in both the quality and comparability of the data.
In our tightly wired world, business executives make decisions under pressure. Almost always, these decisions must be made with less than complete information. This course is about how to effectively use data that is currently available (or can be obtained within a reasonable time frame and cost) to improve business decision-making. We will use business examples from functional areas such as finance, marketing, human resources, and operations to illustrate the role of data analysis in decision making. This course is not designed to be a dry sleepy-time set of abstract, mathematical lectures.
