Sandsynlighedsregning og statistik

I anledning af den seneste reform af læreruddannelsen er Matematik for lærerstuderende nu blevet målrettet de nye krav. Stokastik 1.-10. klasse præsenterer fagligt og fagdidaktisk materiale samt tilhørende arbejdsopgaver svarende til ét modul efter LU13. Stokastik er det, der i skolen hedder sandsynlighedsregning og statistik. Da der er stort overlap mellem kravene i undervisningsfaget matematik 1.-6. klasse og undervisningsfaget matematik 4.-10. klasse, dækker bogen begge disse faglige specialiseringer. Den såkaldte stofdidaktik, der er knyttet til bogens faglige emner, findes i særlige kapitler, mens det fagdidaktiske stof, der er fælles for al matematikundervisning, skal søges i to andre bøger i systemet: Fagdidaktikken findes i Delta, og bogen My dækker elever med særlige behov.

Statistik for ikke-statistikere er en kort introduktion til statistik. Bogen er en 2. udgave og forklarer statistikken, så den er til at forstå. Den viser konsekvent, hvad statistikken kan bruges til, og forudsætter blot, at du kan bruge en lommeregner. Den er forsynet med talrige eksempler. Den gennemgår indsamling, bearbejdning, analyse og præsentation af data. OBS! Ny udgave i oktober 2017, brug SBN 9788759329450

Introduktion til statistik med SPSS giver dig et grundigt blik ned i maskinrummet på statistikprogrammet SPSS, og du får samtidig et godt metodisk og teoretisk fundament til at kunne udføre fornuftige kvantitative analyser. Bogen er en praksisorienteret bog, som hverken kræver, at du er it-nørd eller matematik-haj for at komme i gang med at forstå og anvende statistik og SPSS."En stor force ved bogen er, at den ikke nøjes med at forklare, hvad man skal kigge efter i et output - men også forklarer hvad hele outputtet betyder. Dermed sidder man ikke med en tom følelse af bare at være sluppet igennem hvor gærdet er lavest. Man får derimod mulighed for, gennem korte og præcise, og rigt illustrerede (illustrationer fra SPSS) eksempler at følge eksempler til dørs." Stud.scient.pol Thomas Emil Jensen

En introduktion til statistikprogrammet R. Bogen introducerer brugeren for programmets basale elementer og præsenterer derefter deres anvendelse til statistisk analyse.R er et statistikprogram, der bruges og udvikles af statistikere over hele verden. Det er sandsynligvis det førende statistikprogram, i det mindste blandt statistikere, og det er gratis at anvende og frit tilgængeligt.Denne bog er rettet mod nye brugere af programmet. Med afsæt i biovidenskaberne behandler bogen gængse dataproblematikker og statistiske modeller.

Denne formelsamling er udarbejdet med henblik på at kunne anvendes i forbindelse med statistikundervisningen på erhvervsskolernes korte videregående uddannelser (erhvervsakademiuddannelserne ), på HD og HA, og den anvendes på andre studier med et tilsvarende statistikpensum.Formelsamlingen giver, på begrænset plads, et overblik over de metoder, der er til rådighed, når man skal løse et statistisk problem.

BIOSTATISTIK & EPIDEMIOLOGIBag sundhedsvidenskabelige undersøgelser er indsamlet en lang række data. Det er en videnskabelig disciplin at gøre data overskuelige, håndtér- og analysérbare på korrekt vis, så sammenhænge mellem f.eks. adfærd og sundhed er til at forstå i et udsagn som: ”Mandlige rygere har 50 % større risiko for blodpropper”. Hvordan når man frem til det resultat? Og holder det?BIOSTATISTIK & EPIDEMIOLOGI yder læseren en forståelse af statistikken og epidemiologiens grundbegreber samt mulighed for at mestre basale værktøjer til beskrivelse af egne observationer. Første del af bogen er tilegnet statistiske begreber og analyser, f.eks. kategorisering af data og typer af tests, mens anden del af bogen beskæftiger sig med principperne bag forskning og studiedesigns. Undervejs kan læseren afprøve egne beregninger, teste sin viden, og bogens overskuelige struktur og grundige indeksikalisering gør den velegnet som opslagsværk og til støtte, når begreber fra videnskabelige artikler skal læses og forstås.Bogen henvender sig primært til medicinstuderende ved landets fire fakulteter i København, Odense, Aarhus og Aalborg, men andre faggrupper, såsom odontologi, farmaci, humanbiologi og folkesundhedsvidenskab, vil også finde de beskrevne principper anvendelige som introduktion til basal statistik og epidemiologi.

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. Youll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what youve learned along the way.Youll learn how to:Wrangletransform your datasets into a form convenient for analysisProgramlearn powerful R tools for solving data problems with greater clarity and easeExploreexamine your data, generate hypotheses, and quickly test themModelprovide a low-dimensional summary that captures true "e;signals"e; in your datasetCommunicatelearn R Markdown for integrating prose, code, and results

As a comprehensive textbook in survey sampling, this book discusses the inadequacies of classic, designed-based inferential procedures and provides alternative approaches in the form of model formulations, model-design-based procedures of analysis, inference and interpretation. The book focuses on a wide range of topics which included Bayesian and Empirical Bayesian approaches, complex procedures of stratification, clustering, sampling in multi stages and phases, linear and non-linear estimation of parameters, small area estimation by spatial and chronological modelling, network and adaptive sampling methods and more. The book includes detailed case studies and exercises, making it valuable for students of statistics, specifically survey sampling.

This book provides a thorough conversation on the underpinnings of Covid-19 spread modelling by using stochastics nonlocal differential and integral operators with singular and non-singular kernels. The book presents the dynamic of Covid-19 spread behaviour worldwide. It is noticed that the spread dynamic followed process with nonlocal behaviours which resemble power law, fading memory, crossover and stochastic behaviours. Fractional stochastic differential equations are therefore used to model spread behaviours in different parts of the worlds. The content coverage includes brief history of Covid-19 spread worldwide from December 2019 to September 2021, followed by statistical analysis of collected data for infected, death and recovery classes.

¿¿Non-parametric methods are widely used for studying populations that take on a ranked order (such as movie reviews receiving one to four stars). The use of non-parametric methods may be necessary when data have a ranking but no clear numerical interpretation, such as when assessing preferences. In terms of levels of measurement, non-parametric methods result in "ordinal" data. As non-parametric methods make fewer assumptions, their applicability is much wider than the corresponding parametric methods. In particular, they may be applied in situations where less is known about the application in question. Also, due to the reliance on fewer assumptions, non-parametric methods are more robust. Non-parametric methods have many popular applications, and are widely used in research in the fields of the behavioral sciences and biomedicine. This is a textbook on non-parametric statistics for applied research. The authors propose to use a realistic yet mostly fictional situation and series of dialogues to illustrate in detail the statistical processes required to complete data analysis. This book draws on a readers existing elementary knowledge of statistical analyses to broaden his/her research capabilities. The material within the book is covered in such a way that someone with a very limited knowledge of statistics would be able to read and understand the concepts detailed in the text.The ¿real world¿ scenario to be presented involves a multidisciplinary team of behavioral, medical, crime analysis, and policy analysis professionals work together to answer specific empirical questions regarding real-world applied problems. The reader is introduced to the team and the data set, and through the course of the text follows the team as they progress through the decision making process of narrowing the data and the research questions to answer the applied problem. In this way, abstract statistical concepts are translated into concrete and specific language.This text uses one data set from which all examples are taken. This is radically different from other statistics books which provide a varied array of examples and data sets. Using only one data set facilitates reader-directed teaching and learning by providing multiple research questions which are integrated rather than using disparate examples and completely unrelated research questions and data.

The study of quantum disorder has generated considerable research activity in mathematics and physics over past 40 years. While single-particle models have been extensively studied at a rigorous mathematical level, little was known about systems of several interacting particles, let alone systems with positive spatial particle density. Creating a consistent theory of disorder in multi-particle quantum systems is an important and challenging problem that largely remains open. Multi-scale Analysis for Random Quantum Systems with Interaction  presents the progress that had been recently achieved in this area.  The main focus of the book is on a rigorous derivation of the multi-particle localization in a strong random external potential field. To make the presentation accessible to a wider audience, the authors restrict attention to a relatively simple tight-binding Anderson model on a cubic lattice Zd.  This book includes the following cutting-edge features: an introduction to the state-of-the-art single-particle localization theory an extensive discussion of relevant technical aspects of the localization theorya thorough comparison of the multi-particle model with its single-particle counterpart a self-contained rigorous derivation of both spectral and dynamical localization in the multi-particle tight-binding Anderson model.  Required mathematical background for the book includes a knowledge of functional calculus, spectral theory (essentially reduced to the case of finite matrices) and basic probability theory. This is an excellent text for a year-long graduate course or seminar in mathematical physics. It also can serve as a standard reference for specialists.

¿In this brief we consider some stochastic models that may be used to study problems related to environmental matters, in particular, air pollution.  The impact of exposure to air pollutants on people's health is a very clear and well documented subject. Therefore, it is very important to obtain ways to predict or explain the behaviour of pollutants in general. Depending on the type of question that one is interested in answering, there are several of ways studying that problem. Among them we may quote, analysis of the time series of the pollutants' measurements, analysis of the information obtained directly from the data, for instance, daily, weekly or monthly averages and standard deviations. Another way to study the behaviour of pollutants in general is through mathematical models. In the mathematical framework we may have for instance deterministic or stochastic models. The type of models that we are going to consider in this brief are the stochastic ones.¿