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Esta monografía proporciona un resumen de las herramientas básicas de estadística descriptiva e inferencia estadística,con un apartado dedicado al análisis de supervivencia. Se presentan 3 ejemplos de aplicación de las técnicas con datos reales del ámbito clínico usando el programa estadístico SPSS. Está pensada para usuarios que quieran recordar de forma sencilla y rápida los conceptos básicos de estadística descriptiva y contrastes de hipótesis, así como tener una guía de qué técnica aplicar en función del problema a resolver. El capítulo dedicado al análisis de supervivencia está especialmente destinado a las personas interesadas en disponer de una guía práctica de cómo realizar este análisis con SPSS. Los ejemplos ilustrados son del ámbito de las Ciencias de la Salud, lo que puede ser especialmente útil, aunque no exclusivo, para todos los interesados de este ámbito.

Survival analysis (Biometry)

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The aim of this atlas is to present summarised information and to illustrate comprehensively the shell morphology and structure of the majority of recorded Sphagnum-dwelling testate amoebae in Bulgaria (a total of 120 species, each of them illustrated with 9 LM and SEM photos). Since most of these species appear to be widely distributed in Europe, as well as in many other regions of the world, the atlas may be of interest to all researchers on testate amoebae and can also be used by specialists in ecology, hydrobiology, palaeoecology and environmental monitoring.

biometry --- palaeoecology and environmental monitoring --- ecology --- hydrobiology --- Sphagnum-dwelling testate amoebae --- ultramorphology --- Bulgaria

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This open access book offers an introduction to mixed generalized linear models with applications to the biological sciences, basically approached from an applications perspective, without neglecting the rigor of the theory. For this reason, the theory that supports each of the studied methods is addressed and later - through examples - its application is illustrated. In addition, some of the assumptions and shortcomings of linear statistical models in general are also discussed. An alternative to analyse non-normal distributed response variables is the use of generalized linear models (GLM) to describe the response data with an exponential family distribution that perfectly fits the real response. Extending this idea to models with random effects allows the use of Generalized Linear Mixed Models (GLMMs). The use of these complex models was not computationally feasible until the recent past, when computational advances and improvements to statistical analysis programs allowed users to easily, quickly, and accurately apply GLMM to data sets. GLMMs have attracted considerable attention in recent years. The word "Generalized" refers to non-normal distributions for the response variable and the word "Mixed" refers to random effects, in addition to the fixed effects typical of analysis of variance (or regression). With the development of modern statistical packages such as Statistical Analysis System (SAS), R, ASReml, among others, a wide variety of statistical analyzes are available to a wider audience. However, to be able to handle and master more sophisticated models requires proper training and great responsibility on the part of the practitioner to understand how these advanced tools work. GMLM is an analysis methodology used in agriculture and biology that can accommodate complex correlation structures and types of response variables.

Biometry. --- Multivariate analysis. --- Regression analysis. --- Agriculture. --- Biostatistics. --- Multivariate Analysis. --- Linear Models and Regression. --- Farming --- Husbandry --- Industrial arts --- Life sciences --- Food supply --- Land use, Rural --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Multivariate distributions --- Multivariate statistical analysis --- Statistical analysis, Multivariate --- Analysis of variance --- Mathematical statistics --- Matrices --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Biomathematics --- Statistics --- Statistical methods --- Generalized Linear Mixed Models --- non normal distribution --- GLM --- GLMM --- Model Inference --- non normal response

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Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study.

online signature verification --- shape contexts --- function features --- SC-DTW --- symbolic representation --- two-stage method --- finger features --- multimodal recognition --- local coding --- Gabor filter --- LGS --- human identification --- biomarker --- ECG --- machine learning --- Physionet --- Lviv Biometric Dataset --- biometry --- identification --- bloodstream --- image recognition --- multi-biometrics --- bit planes --- block --- mutual information --- cross-device --- dorsal hand vein recognition --- person re-identification --- superpixel --- temporally aligned pooling --- walking cycle --- automatic recognition --- face --- voice --- body motion --- autism spectrum disorder (ASD) --- assessment --- intervention --- curve similarity --- curve similarity model --- curve similarity transformation --- similarity distance --- segmentation matching --- evolutionary computation --- finger vein recognition --- hand vein recognition --- contactless acquisition device --- public vascular pattern dataset --- biometric recognition performance evaluation --- face verification --- optical correlation --- Hausdorff distance --- image classification --- face detection --- depth map ensemble --- filtering --- geometric deep learning --- ear detection --- structured prediction --- semantic segmentation --- rotation equivariance --- Gaussian mixture model --- superpixels --- face recognition systems --- person identification --- biometric systems --- survey --- automatic signature verification --- touch-screen sensor --- data quality --- enrollment phase --- performance assessment --- augmented signature --- security enhancement --- mobile conditions --- biometric recognition --- visible light iris images --- image quality assessment --- image covariates --- quality filtering --- vascular biometric recognition --- wrist vein recognition --- contactless dataset --- pattern recognition --- infrared camera --- non-contact devices --- Scale-Invariant Feature Transform (SIFT®) --- Speeded Up Robust Features (SURF®) --- Oriented FAST and Rotated BRIEF (ORB) --- fingerprint --- presentation attack detection --- deep learning