Software Testing, Second Edition provides practical insight into the world of software testing and quality assurance. Learn how to find problems in any computer program, how to plan an effective test approach and how to tell when software is ready for release. Updated from the previous edition in 2000 to include a chapter that specifically deals with testing software for securi...(展开全部)

PSYCHOLOGICAL TESTING: PRINCIPLES, APPLICATIONS, AND ISSUES, Eighth Edition, discusses the fundamentals of psychological testing and examines test applications as well as present-day testing controversies.

The third edition of Testing Statistical Hypotheses updates and expands upon the classic graduate text, emphasizing optimality theory for hypothesis testing and confidence sets. The principal additions include a rigorous treatment of large sample optimality, together with the requisite tools. In addition, an introduction to the theory of resampling methods such as the bootstrap...(展开全部)

Usability testing is a subdiscipline of User Experience. Its goal is to ensure that a given product is easy to use and the user's experience with the product is intuitive and satisfying. Usability studies are conducted with study participants who are representative of the target users to gather feedback on a user interface. The feedback is then used to refine and improve the user interface.Remote studies involve fewer logistics, allow participation regardless of location and are quicker and cheaper to execute compared to in person studies, while delivering valuable insights. The users are not inhibited by being in a new environment under observation; they can act naturally in their familiar environment. Remote unmoderated studies additionally have the advantage of being independent of time zones.This book will teach you how to conduct qualitative remote usability studies, in particular remote moderated and unmoderated studies. Each chapter provides actionable tips on how to use each methodology and how to compensate for the specific nature of each methodology. The book also provides material to help with planning and executing each study type.

Testing Statistical Hypotheses, 4th Edition updates and expands upon the classic graduate text, now a two-volume work. The first volume covers finite-sample theory, while the second volume discusses large-sample theory. A definitive resource for graduate students and researchers alike, this work grows to include new topics of current relevance. New additions include an expanded...(展开全部)

Significance testing - a core technique in statistics for hypothesis testing - is introduced in this volume. Mohr first reviews what is meant by sampling and probability distributions and then examines in-depth normal and t-tests of significance. The uses and misuses of significance testing are also explored.

Sending information via the internet is not entirely private, as evidenced by the rise in hacking, malware attacks, and security threats. With the help of this book, you'll learn crucial penetration testing techniques to help you evaluate enterprise defenses.You'll start by understanding each stage of pentesting and deploying target virtual machines, including Linux and Windows. Next, the book will guide you through performing intermediate penetration testing in a controlled environment. With the help of practical use cases, you'll also be able to implement your learning in real-world scenarios. By studying everything from setting up your lab, information gathering and password attacks, through to social engineering and post exploitation, you'll be able to successfully overcome security threats. The book will even help you leverage the best tools, such as Kali Linux, Metasploit, Burp Suite, and other open source pentesting tools to perform these techniques. Toward the later chapters, you'll focus on best practices to quickly resolve security threats.By the end of this book, you'll be well versed with various penetration testing techniques so as to be able to tackle security threats effectively

The third edition of Testing Statistical Hypotheses updates and expands upon the classic graduate text, emphasizing optimality theory for hypothesis testing and confidence sets. The principal additions include a rigorous treatment of large sample optimality, together with the requisite tools. In addition, an introduction to the theory of resampling methods such as the bootstrap...(展开全部)

Testing Statistical Hypotheses, 4th Edition updates and expands upon the classic graduate text, now a two-volume work. The first volume covers finite-sample theory, while the second volume discusses large-sample theory. A definitive resource for graduate students and researchers alike, this work grows to include new topics of current relevance. New additions include an expanded...(展开全部)