Description 
1 online resource 
Contents 
Probability  Random variables and random vectors  Probability models  Parametric point estimation  Likelihood based estimation  Hypothesis testing  Generalized linear models 
Summary 
Presents a unified approach to parametric estimation, confidence intervals, hypothesis testing, and statistical modeling, which are uniquely based on the likelihood function This book addresses mathematical statistics for upperundergraduates and first year graduate students, tying chapters on estimation, confidence intervals, hypothesis testing, and statistical models together to present a unifying focus on the likelihood function. It also emphasizes the important ideas in statistical modeling, such as sufficiency, exponential family distributions, and large sample properties. Mathematical Statistics: An Introduction to Likelihood Based Inference makes advanced topics accessible and understandable and covers many topics in more depth than typical mathematical statistics textbooks. It includes numerous examples, case studies, a large number of exercises ranging from drill and skill to extremely difficult problems, and many of the important theorems of mathematical statistics along with their proofs. In addition to the connected chapters mentioned above, Mathematical Statistics covers likelihoodbased estimation, with emphasis on multidimensional parameter spaces and range dependent support. It also includes a chapter on confidence intervals, which contains examples of exact confidence intervals along with the standard large sample confidence intervals based on the MLE's and bootstrap confidence intervals. There's also a chapter on parametric statistical models featuring sections on noniid observations, linear regression, logistic regression, Poisson regression, and linear models. Prepares students with the tools needed to be successful in their future work in statistics data science Includes practical case studies including reallife data collected from Yellowstone National Park, the Donner party, and the Titanic voyage Emphasizes the important ideas to statistical modeling, such as sufficiency, exponential family distributions, and large sample properties Includes sections on Bayesian estimation and credible intervals Features examples, problems, and solutions Mathematical Statistics: An Introduction to Likelihood Based Inference is an ideal textbook for upperundergraduate and graduate courses in probability, mathematical statistics, and/or statistical inference 
Bibliography 
Includes bibliographical references and index 
Notes 
Online resource; title from digital title page (viewed on March 5, 2019) 
Subject 
Mathematical statistics


MATHEMATICS  Applied.


MATHEMATICS  Probability & Statistics  General.


Mathematical statistics.

Form 
Electronic book

LC no. 
2018010628 
ISBN 
9781119385288 

9781118770979 

9781118771075 

9781118771167 
