Textbook in PDF format This book is aimed at those in engineering/scientific fields who have never learned programming before but are eager to master the C language quickly so as to immediately apply it to problem solving in numerical analysis. The book skips unnecessary formality but explains all the important aspects of C essential for numerical analysis. Topics covered in numerical analysis include single and simultaneous equations, differential equations, numerical integration, and simulations by random numbers. In the Appendices, quick tutorials for gnuplot, Octave/MatLAB, and FORTRAN for C users are provided. For the second edition, a section on memory management was added. Exercise problems were updated and the numerical analysis part refined. Python is becoming more popular as a versatile, general-purpose language and is increasingly seen as a good starting point for students. Among the many modern programming languages, using C for scientific and engineering computations is still beneficial. C covers almost all the basic concepts and syntax found in modern programming languages, except for object-oriented programming, which is used in languages such as C++ and Java. Those who learn C as their first language often find it easy to pick up other programming languages and tools, including MatLAB. However, the reverse is not true. A key advantage of C is that it is a compiled language, making it preferable to interpreted languages for scientific and engineering tasks. While there are many excellent textbooks on C and numerical analysis, finding one that effectively combines both topics is difficult. This book is not meant to be a comprehensive reference to C or numerical analysis. Instead, it focuses on the C features essential for numerical analysis, intentionally leaving out features not directly related to this purpose. This book does not cover C++, as the benefits of object-oriented programming in numerical analysis are minimal. By the end of this book, readers will be able to solve various engineering and science problems by writing their own C programs. The book is structured into two parts. In Part I, comprehensive coverage of the general syntax of the C language is provided. The compiler utilized throughout is gcc, which is freely available on nearly all platforms. Given that gcc is native to the Unix environment, a concise introduction to the Unix operating system is included. Part II focuses on key topics in numerical analysis, accompanied by detailed explanations and listings of corresponding C programs. The subjects covered include solving single equations, numerical differentiation, numerical integration, solving a set of simultaneous equations, and solving differential equations