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 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.

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.