Some entries relating to statistical aspects of research are also used so as to help the researcher in the successful formulation, analysis, and execution of the research design and carry the same towards its logical end. This book makes use of approximately entries on the key concepts and issues of research with cross references where necessary. This volume is designed to appeal to undergraduate and graduate students, teachers, lecturers, practitioners, researchers, consultants, and consumers of information across the field of applied linguistics and other related disciplines.
Christopher uses published research with inherently interesting social sciences content to help students make clear connections between statistics and real life. Using a friendly, easy-to-understand presentation, Christopher walks students through the hand calculations of key statistical tools and provides step-by-step instructions on how to run the appropriate analyses for each type of statistic in SPSS and how to interpret the output. With the premise that a conceptual grasp of statistical techniques is critical for students to truly understand why they are doing what they are doing, the author avoids overly formulaic jargon and instead focuses on when and how to use statistical techniques appropriately.
The book is a starting point for those involved in such research and covers the methods needed to design, analyze, and interpret bioequivalence trials; explores when, how, and why these studies are performed as part of drug development; and demonstrates the methods using real world examples.
Drawing on knowledge gained directly from working in the pharmaceutical industry, the authors set the stage by describing the general role of statistics. Once the foundation of clinical pharmacology drug development, regulatory applications, and the design and analysis of bioequivalence trials are established, including recent regulatory changes in design and analysis and in particular sample-size adaptation, they move on to related topics in clinical pharmacology involving the use of cross-over designs.
These include, but are not limited to, safety studies in Phase I, dose-response trials, drug interaction trials, food-effect and combination trials, QTc and other pharmacodynamic equivalence trials, proof-of-concept trials, dose-proportionality trials, and vaccines trials. This second edition addresses several recent developments in the field, including new chapters on adaptive bioequivalence studies, scaled average bioequivalence testing, and vaccine trials. Purposefully designed to be instantly applicable, Bioequivalence and Statistics in Clinical Pharmacology, Second Edition provides examples of SAS and R code so that the analyses described can be immediately implemented.
The authors have made extensive use of the proc mixed procedures available in SAS. Topics include for example sample size, the interviewing relationship, hypothesis testing, and report formats. The second edition features a new section on using Internet surveys. Systematic, rigorous research is needed if the growing field of language learning is to progress methodically. This book demonstrates and fully explains such a methodology.
Given that research in language acquisition yields practical pedagogical implications, it is crucial that it is rigorous and accurate. This book offers a quantitative research methodology that relies on statistical analysis in order to make inferences and conclusions about language learning.
Experimental research aims to understand differences between or within groups of learners under manipulated environments. It requires strict control of conditions, enabling interpretations with a low factor of error.
Aek Phakiti provides step-by-step guidelines and underlying principles, epistemology and methodology, in a book that is essential for advanced students of language acquisition and language and education.
You cannot develop a deep understanding and application of machine learning without it. Cut through the equations, Greek letters, and confusion, and discover the topics in statistics that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover the importance of statistical methods to machine learning, summary stats, hypothesis testing, nonparametric stats, resampling methods, and much more.
Treleaven Publisher: Elsevier Health Sciences ISBN: Category: Medical Page: View: A guide to the practice of stem cell transplantation, its status in the treatment of various disorders and the problems that arise after transplantation, aimed at the whole transplant team. An up to date guide to best practice in the use of stem cell transplantation, covering current status in the treatment of malignant and non-malignant conditions, practical aspects and problems such as infection and graft versus host disease.
Has a practical, accessible approach with free use of algorithms, list tables. Aimed at the whole transplant team - this is an interdisciplinary field. Illustrated in colour throughout. Genres: Mathematics. This introductory textbook provides an inexpensive, brief overview of statistics to help readers gain a better understanding of how statistics work and how to interpret them correctly.
Each chapter describes a different statistical technique, ranging from basic concepts like central tendency and describing distributions to more advanced concepts such as t tests, regression, repeated-measures ANOVA, and factor analysis.
Each chapter begins with a short description of the statistic and when it should be used. This is followed by a more in-depth explanation of how the statistic works. Drawing on knowledge gained directly from working in the pharmaceutical industry, the authors set the stage by describing the general role of statistics.
Once the foundation of clinical pharmacology drug development, regulatory applications, and the design and analysis of bioequivalence trials are established, including recent regulatory changes in design and analysis and in particular sample-size adaptation, they move on to related topics in clinical pharmacology involving the use of cross-over designs.
These include, but are not limited to, safety studies in Phase I, dose-response trials, drug interaction trials, food-effect and combination trials, QTc and other pharmacodynamic equivalence trials, proof-of-concept trials, dose-proportionality trials, and vaccines trials. This second edition addresses several recent developments in the field, including new chapters on adaptive bioequivalence studies, scaled average bioequivalence testing, and vaccine trials.
Purposefully designed to be instantly applicable, Bioequivalence and Statistics in Clinical Pharmacology, Second Edition provides examples of SAS and R code so that the analyses described can be immediately implemented.
The authors have made extensive use of the proc mixed procedures available in SAS. This textbook takes students through each stage of designing and conducting marketing research and interpreting the resulting data.
Topics include for example sample size, the interviewing relationship, hypothesis testing, and report formats. The second edition features a new section on using Internet surveys. Language learning research aims to describe and fully explain how and why language learning takes place, but can fall short of its stated purpose. Systematic, rigorous research is needed if the growing field of language learning is to progress methodically.
This book demonstrates and fully explains such a methodology. Given that research in language acquisition yields practical pedagogical implications, it is crucial that it is rigorous and accurate. This book offers a quantitative research methodology that relies on statistical analysis in order to make inferences and conclusions about language learning.
Experimental research aims to understand differences between or within groups of learners under manipulated environments. It requires strict control of conditions, enabling interpretations with a low factor of error. Aek Phakiti provides step-by-step guidelines and underlying principles, epistemology and methodology, in a book that is essential for advanced students of language acquisition and language and education.
Statistics is a pillar of machine learning. You cannot develop a deep understanding and application of machine learning without it. Cut through the equations, Greek letters, and confusion, and discover the topics in statistics that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover the importance of statistical methods to machine learning, summary stats, hypothesis testing, nonparametric stats, resampling methods, and much more.
A guide to the practice of stem cell transplantation, its status in the treatment of various disorders and the problems that arise after transplantation, aimed at the whole transplant team.
An up to date guide to best practice in the use of stem cell transplantation, covering current status in the treatment of malignant and non-malignant conditions, practical aspects and problems such as infection and graft versus host disease.
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