This eBook was written as the sequel to the eBook titled DC …
This eBook was written as the sequel to the eBook titled DC Circuits, which was written in 2016 by Chad Davis. This eBook covers Alternating Current (AC) circuit theory as well us a brief introduction of electronics. It is broken up into seven modules. Module 1 covers the basic theory of AC signals. Since only DC sources are used in the first eBook, details of AC signals such as sinusoidal waveforms (or sine waves), square waves, and triangle waves are provided. Module 2, titled AC Circuits Math Background, covers the mathematics background needed for solving AC circuit problems. The background material in Modules 1 and 2 are combined in Module 3 to solve circuits with AC sources that include resistors, inductors, and capacitors (RLC circuits).
This book covers Direct Current (DC) circuit theory and is broken up …
This book covers Direct Current (DC) circuit theory and is broken up into three modules. Module 1 covers the basics for circuits that include DC sources (voltage or current) and resistors. Even though Module 1 is not very difficult, it forms the foundation for more complicated topics in modules 2 and 3 so it is important to have a firm grasp of all Module 1 topics before moving on. Module 2 covers more difficult problem solving techniques for circuits that include only DC sources and resistors. Module 3 introduces capacitors and inductors. These non-linear reactive components are analyzed in the transient and steady state regions in circuits with DC sources in Module 3. Also annexed is a two-page cheat sheet that ENGR 2431 students at University of Oklahoma can use for exams.
Measurement and instrumentation are fundamental elements of many engineering projects. From research, …
Measurement and instrumentation are fundamental elements of many engineering projects. From research, to development, to manufacturing, to user products, engineers are constantly needing to measure things: brightness of a light, dimensions of an object, separation between things, frequency content, stress, strain, pressure, voltage, etc. In the real world measuring systems are not perfect, so the results of a measurement are only an estimate of the true value. Instrumentation for making measurements relies on some fundamental assumptions to ensure the veracity of the measurements. Some key elements are: bandwidth, sampling rate, dynamic range, sensor type, etc. This text discusses the basic concepts of what a measurement is, how the instrumentation chosen (or developed) can affect the measurement, and how to deal with the measurement error that is in all instrumentation systems. Topics include data acquisition, signal conditioning, sensor types, and measurement noise and its various noise distributions. The text concludes with three user projects that bring together these topics into an informative work that reinforces the theory.
The focus of this book is on using quantitative research methods to …
The focus of this book is on using quantitative research methods to test hypotheses and build theory in political science, public policy and public administration. It is designed for advanced undergraduate courses, or introductory and intermediate graduate-level courses. The first part of the book introduces the scientific method, then covers research design, measurement, descriptive statistics, probability, inference, and basic measures of association. The second part of the book covers bivariate and multiple linear regression using the ordinary least squares, the calculus and matrix algebra that are necessary for understanding bivariate and multiple linear regression, the assumptions that underlie these methods, and then provides a short introduction to generalized linear models.
The book fully embraces the open access and open source philosophies. The book is freely available in the SHAREOK repository; it is written in R Markdown files that are available in a public GitHub repository; it uses and teaches R and RStudio for data analysis, visualization and data management; and it uses publically available survey data (from the Meso-Scale Integrated Socio-geographic Network) to illustrate important concepts and methods. We encourage students to download the data, replicate the examples, and explore further! We also encourage instructors to download the R Markdown files and modify the text for use in different courses.
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