Bøger af Richard J. (Montana Tech Rossi

APPLIED BIOSTATISTICS FOR THE HEALTH SCIENCESIn this newly revised edition of Applied Biostatistics for the Health Sciences, accomplished statistician Dr. Richard Rossi delivers a robust and easy-to-understand exploration of statistics in the context of applied health science and biostatistics. The book covers sample design, logistic regression, experimental design, survival analysis, basic statistical computation, and many more topics with a strong focus on the correct use and interpretation of statistics. The author also explains how to assess the quality of observed data, how to collect quality data, and the use of confidence intervals in conjunction with hypothesis and significance tests.* A thorough introduction to biostatistics, including explanations of fundamental concepts like populations, samples, statistics, biomedical studies, and data set examples* A comprehensive exploration of population descriptions, including qualitative and quantitative variables, multivariate data, measures of dispersion, and probability* Practical discussions of random sampling, summarizing random samples, and the measurement of the reliability of statistics* In-depth examinations of confidence intervals, statistical hypothesis testing, simple and multiple linear regression, and experimental designPerfect for health science and biostatistics students and professors at the upper undergraduate and graduate levels, Applied Biostatistics for the Health Sciences is also a must-read reference for practitioners and professionals in the fields of pharmacy, biochemistry, nursing, health care informatics, and the applied health sciences.

Präsentiert eine einheitliche Herangehensweise an die parametrische Schätzung, Konfidenzintervalle, Hypothesentests und statistische Modelle, die in einzigartiger Weise auf der Likelihood-Funktion basieren.Dieses Fachbuch beschäftigt sich mit der mathematischen Statistik für Studenten im höheren Grundstudium und zu Beginn des Hauptstudiums. Die Kapitel zu Schätzung, Konfidenzintervallen, Hypothesentests und statistischen Modellen zusammengenommen legen den Schwerpunkt auf die Likelihood-Funktion. Wichtige Aspekte statistischer Modelle, wie Suffizienz, Verteilungen in der Exponentialfamilie und Eigenschaften großer Stichproben, stehen ebenfalls im Vordergrund. Mathematical Statistics: An Introduction to Likelihood Based Inference macht komplexe Themen zugänglich und verständlich, deckt viele Themen ausführlicher ab als herkömmliche Lehrbücher zur mathematischen Statistik. Das Buch enthält unzählige Beispiele, Fallstudien, Übungen (von einfach bis schwierig) sowie viele wichtige Theoreme der mathematischen Statistik, inklusive deren Nachweise.

The primary purpose of this text is to introduce math majors, who have completed a calculus sequence, to the axiomatic makeup of modern mathematics. Heavy emphasis is placed on the writing of clear and understandable proofs.