This book presents basic tools from probability theory used in algorithmic applications, with concrete examples.For many applications a randomized algorithm is the simplest algorithm available, or the fastest, or both. This book presents basic tools from probability theory used in algorithmic applications, with examples to illustrate the use of each tool in a concrete setting. Several important areas of application of randomized algorithms are explored in detail, giving a representative selection of the algorithms in these areas. Although written primarily as a text, this book should also prove invaluable as a reference for professionals and researchers.For many applications a randomized algorithm is the simplest algorithm available, or the fastest, or both. This book presents basic tools from probability theory used in algorithmic applications, with examples to illustrate the use of each tool in a concrete setting. Several important areas of application of randomized algorithms are explored in detail, giving a representative selection of the algorithms in these areas. Although written primarily as a text, this book should also prove invaluable as a reference for professionals and researchers.For many applications, a randomized algorithm is either the simplest or the fastest algorithm available, and sometimes both. This book introduces the basic concepts in the design and analysis of randomized algorithms. The first part of the text presents basic tools such as probability theory and probabilistic analysis that are frequently used in algorithmic applications. Algorithmic examples are also given to illustrate the use of each tool in a concrete setting. In the second part of the book, each chapter focuses on an important area to which randomized algorithms can be applied, providing a comprehensive and representative selection of the algorithms that might be used in each of these areas. Although written primarily as a text for advanced undergraduates and graduate stul£ž