Provides a Solid Foundation for Statistical Modeling and Inference and Demonstrates Its Breadth of Applicability Stochastic Modeling and Mathematical Statistics: A Text for Statisticians and Quantitative Scientists addresses core issues in post-calculus probability and statistics in a way that is useful for statistics and mathematics majors as well as students in the quantitative sciences. The bookas conversational tone, which provides the mathematical justification behind widely used statistical methods in a reader-friendly manner, and the bookas many examples, tutorials, exercises and problems for solution, together constitute an effective resource that students can read and learn from and instructors can count on as a worthy complement to their lectures. Using classroom-tested approaches that engage students in active learning, the text offers instructors the flexibility to control the mathematical level of their course. It contains the mathematical detail that is expected in a course for qmajorsq but is written in a way that emphasizes the intuitive content in statistical theory and the way theoretical results are used in practice. More than 1000 exercises and problems at varying levels of difficulty and with a broad range of topical focus give instructors many options in assigning homework and provide students with many problems on which to practice and from which to learn.Suppose that the single observation X is drawn from a distribution FIc with pdf fIc(x ) = 2(1aIc)x+Ic for 0 alt; x alt; 1, where Ic can take any ... (a) Find the best test of size Ip for testing H0: Ic = 1/2 vs. ... Suppose that a random sample of size n = 25 was drawn from a normal population with unknown mean I¼ and known variance 100.
|Title||:||Stochastic Modeling and Mathematical Statistics|
|Author||:||Francisco J. Samaniego|
|Publisher||:||CRC Press - 2014-01-14|