This textbook is an introductory coverage of algorithms and data structures with application to graphics and geometry.
This is a free textbook teaching introductory statistics for undergraduates in Psychology. This textbook is part of a larger OER course package for teaching undergraduate statistics in Psychology, including this textbook, a lab manual, and a course website. All of the materials are free and copiable, with source code maintained in Github repositories.
Describe a bivariate relationship's linearity, strength, and direction. In other words, plotting things that take two variables into consideration and trying to see whether there's a pattern with how they relate.
When you combine the sheer scale and range of digital information now available with a journalist’s "nose for news" and her ability to tell a compelling story, a new world of possibility opens up. With The Data Journalism Handbook, you’ll explore the potential, limits, and applied uses of this new and fascinating field.
This valuable handbook has attracted scores of contributors since the European Journalism Centre and the Open Knowledge Foundation launched the project at MozFest 2011. Through a collection of tips and techniques from leading journalists, professors, software developers, and data analysts, you’ll learn how data can be either the source of data journalism or a tool with which the story is told—or both.
The general minimum prerequisite for understanding this book is the intellectual maturity of a junior-level (third-year) college student in an accredited four-year engineering curriculum. A mathematical second-order system is represented in this book primarily by a single second-order ODE, not in the state-space form by a pair of coupled first-order ODEs. Similarly, a two-degrees-of-freedom (fourth-order) system is represented by two coupled second-order ODEs, not in the state-space form by four coupled first-order ODEs. The book does not use bond graph modeling, the general and powerful, but complicated, modern tool for analysis of complex, multidisciplinary dynamic systems. The homework problems at the ends of chapters are very important to the learning objectives, so the author attempted to compose problems of practical interest and to make the problem statements as clear, correct, and unambiguous as possible. A major focus of the book is computer calculation of system characteristics and responses and graphical display of results, with use of basic (not advanced) MATLAB commands and programs. The book includes many examples and homework problems relevant to aerospace engineering, among which are rolling dynamics of flight vehicles, spacecraft actuators, aerospace motion sensors, and aeroelasticity. There are also several examples and homework problems illustrating and validating theory by using measured data to identify first- and second-order system dynamic characteristics based on mathematical models (e.g., time constants and natural frequencies), and system basic properties (e.g., mass, stiffness, and damping). Applications of real and simulated experimental data appear in many homework problems. The book contains somewhat more material than can be covered during a single standard college semester, so an instructor who wishes to use this as a one-semester course textbook should not attempt to cover the entire book, but instead should cover only those parts that are most relevant to the course objectives.
Summary
Introductory Statistics follows scope and sequence requirements of a one-semester introduction to statistics course and is geared toward students majoring in fields other than math or engineering. The text assumes some knowledge of intermediate algebra and focuses on statistics application over theory. Introductory Statistics includes innovative practical applications that make the text relevant and accessible, as well as collaborative exercises, technology integration problems, and statistics labs.
Senior Contributing Authors
Barbara Illowsky, De Anza College
Susan Dean, De Anza College
This is a first draft of a free (as in speech, not as in beer, [Sta02]) (although it is free as in beer as well) textbook for a one-semester, undergraduate statistics course. It was used for Math 156 at Colorado State University–Pueblo in the spring semester of 2017.
This book is about how to read, use, and create maps. Our exploration of maps will be informed by a contextual understanding of how maps reflect the relationship between society and technology, and how mapping is an essential form of scientific and artistic inquiry. We will also explore how mapping is used to address a variety of societal issues, such as land use planning and political gerrymandering. You will gain insight into the technical underpinnings of mapping as a science approach, complement on-going interest and activities, or provide an applied focus for research or policy.
The Principles of Biology sequence (BI 211, 212 and 213) introduces biology as a scientific discipline for students planning to major in biology and other science disciplines. Laboratories and classroom activities introduce techniques used to study biological processes and provide opportunities for students to develop their ability to conduct research.
The goals of this textbook are to help students acquire the technical skills of using software and managing a database, and develop research skills of collecting data, analyzing information and presenting results. We emphasize that the need to investigate the potential and practicality of GIS technologies in a typical planning setting and evaluate its possible applications. GIS may not be necessary (or useful) for every planning application, and we anticipate these readings to provide the necessary foundation for discerning its appropriate use. Therefore, this textbook attempts to facilitate spatial thinking focusing more on open-ended planning questions, which require judgment and exploration, while developing the analytical capacity for understanding a variety of local and regional planning challenges.
While this textbook provides the background for understanding the concepts in GIS as applicable to urban and regional planning, it is best when accompanied by a hands-on tutorial, which will enable readers to develop an in-depth understanding of the specific planning applications of GIS. Chapters in this text book are either composed by the editors using Creative Common materials, or linked to a book chapter scanned copy in the library reserve. In the end of each chapter, we also provided several discussion questions, together with contextual applications through some web links.
Statistical thinking is a way of understanding a complex world by describing it in relatively simple terms that nonetheless capture essential aspects of its structure, and that also provide us some idea of how uncertain we are about our knowledge. The foundations of statistical thinking come primarily from mathematics and statistics, but also from computer science, psychology, and other fields of study.