The A-Z of Error-Free Research

1. Auflage 2012
ISBN: 978-1-4398-9737-9
Verlag: Chapman and Hall/CRC

Buch, Englisch, 269 Seiten, Format (B × H): 140 mm x 216 mm, Gewicht: 344 g

A Practical Guide with Step-by-Step Explanations, Numerous Worked Examples, and R Code
The A–Z of Error-Free Research describes the design, analysis, modeling, and reporting of experiments, clinical trials, and surveys. The book shows you when to use statistics, the best ways to cope with variation, and how to design an experiment, determine optimal sample size, and collect useable data. It also helps you choose the best statistical procedures for your application and takes you step by step through model development and reporting results for publication.

Transition from Student to Researcher
Helping you become a confident researcher, the book begins with an overview of when—and when not—to use statistics. It guides you through the planning and data collection phases and presents various data analysis techniques, including methods for sample size determination. The author then covers techniques for developing models that provide a basis for future research. He also discusses reporting techniques to ensure your research efforts get the proper credit. The book concludes with case-control and cohort studies.

Zielgruppe

Professional Practice & Development

Autoren/Hrsg.

Good, Phillip I.

Fachgebiete

• Sozialwissenschaften Pädagogik Berufliche Bildung Wissenschaftliches Arbeiten, Studientechnik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Interdisziplinäres Wissenschaften Wissenschaften: Allgemeines Wissenschaftliches Arbeiten, Studientechnik
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung

Inhaltsverzeichnis

Research Essentials. Planning: Hypotheses and Losses. Coping with Variation. Experimental Design. Data Collection: Fundamentals. Quality Control. Analyzing Your Data: Describing the Data. Hypothesis Tests. Multiple Variables and Multiple Tests. Miscellaneous Hypothesis Tests. Sample Size Determination. Building a Model: Ordinary Least Squares. Alternate Regression Methods. Decision Trees. Reporting Your Results: Reports. Oral Presentations. Better Graphics. Nonrandom Samples: Cohort and Case-Control Studies. R Primer. Bibliography. Indices.

Über Autor(innen)

Phillip I. Good is a mathematical statistician with nearly 40 years of experience in the field. He has published hundreds of articles on microcomputers and has authored nine books, including A Practitioner’s Guide to Resampling for Data Analysis, Data Mining, and Modeling and Applying Statistics in the Courtroom: A New Approach for Attorneys and Expert Witnesses. He was among the first to apply the bootstrap method in his analyses of 2 × 2 designs with a missing cell. He has also contributed to other areas of small sample statistics, including a uniformly most powerful unbiased permutation test for Type I censored data, an exact test for comparing variances, and an exact test for cross-over designs. He earned a PhD in mathematical statistics from the University of California at Berkeley.