Biostatistics for Clinical and Public Health Research
Auteur : Goodman Melody S.
Biostatistics for Clinical and Public Health Research provides a concise overview of statistical analysis methods. Use of SAS and Stata statistical software is illustrated in full, including how to interpret results.
Focusing on statistical models without all the theory, the book is complete with exercises, case studies, take-away points, and data sets. Readers will be able to maximize their statistical abilities in hypothesis testing, data interpretation, and application while also learning when and how to consult a biostatistician.
This book will be an invaluable tool for students and clinical and public health practitioners.
Descriptive Statistics. Introduction to SAS. Probability. Diagnostics. Discrete Probability Distributions. Continuous Probability Distributions. Probability Distributions. Estimation. One Sample Hypothesis Testing. Two Sample Hypothesis Sample. Nonparametric Statistics. One Sample and Two Sample Hypothesis Testing, Sample Size, and Nonparametric Methods. Categorical Data Sets. ANOVA. Correlation. Linear Regression. Logistic Regression. Survival Analysis. Data Analysis.
Melody S. Goodman, is a biostatistician with experience in study design, developing survey instruments, data collection, data management, and data analysis for public health and clinical research projects. She has taught introductory biostatistics to masters of public health and medical students for over ten years at multiple institutions (Stony Brook University School of Medicine, Washington University in St. Louis School of Medicine, New York University – Global Public Health).
Date de parution : 12-2017
17.4x24.6 cm
Date de parution : 12-2017
17.4x24.6 cm
Disponible chez l'éditeur (délai d'approvisionnement : 14 jours).
Prix indicatif 74,82 €
Ajouter au panierThèmes de Biostatistics for Clinical and Public Health Research :
Mots-clés :
Null Hypothesis; Quantitative research methods; BRFSS; SAS statistical software; Sample Size Calculations; Statistical analysis; CDF; Data sets analysis; SAS Output; Probabilities; Urine Lead Level; Hypothesis testing; BMI Group; PROC TTEST DATA; PROC FREQ DATA; Confidence Interval; SAS Dataset; Blood Lead Levels; YRBSS; Dichotomous Random Variable; Estimated Sample Sizes; Roc Curve; Box Plot; CRP Test; SAS Code; Spearman Rank Correlation Coefficient; Nutrition Examination Survey; Tab Command; Practice Problem; Wilcoxon Signed Rank Test; Pearson’s Chi Squared Test