1.

Record Nr.

UNINA9910467556703321

Autore

De Winter Patricia <1968->

Titolo

Starting out in Statistics [[electronic resource] ] : An Introduction for Students of Human Health, Disease, and Psychology

Pubbl/distr/stampa

Somerset, : Wiley, 2014

ISBN

1-118-92055-4

Descrizione fisica

1 online resource (312 p.)

Altri autori (Persone)

CahusacPeter M. B

Disciplina

610.2/1

Soggetti

Medical statistics -- Textbooks

Medical statistics

Health Care Evaluation Mechanisms

Medicine

Methods

Mathematics

Research

Epidemiologic Methods

Environment and Public Health

Health

Investigative Techniques

Natural Science Disciplines

Science

Population Characteristics

Quality of Health Care

Health Occupations

Health Care

Health Care Quality, Access, and Evaluation

Analytical, Diagnostic and Therapeutic Techniques and Equipment

Disciplines and Occupations

Public Health

Statistics as Topic

Research Design

Health & Biological Sciences

Medical Statistics

Electronic books.

Lingua di pubblicazione

Inglese



Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di contenuto

Starting Out in Statistics; Contents; Introduction - What's the Point of Statistics?; Reference; Basic Maths for Stats Revision; Statistical Software Packages; About the Companion Website; 1 Introducing Variables, Populations and Samples - 'Variability is the Law of Life'; 1.1 Aims; 1.2 Biological data vary; 1.3 Variables; 1.4 Types of qualitative variables; 1.4.1 Nominal variables; 1.4.2 Multiple response variables; 1.4.3 Preference variables; 1.5 Types of quantitative variables; 1.5.1 Discrete variables; 1.5.2 Continuous variables; 1.5.3 Ordinal variables - a moot point

1.6 Samples and populations1.7 Summary; Reference; 2 Study Design and Sampling - 'Design is Everything. Everything!'; 2.1 Aims; 2.2 Introduction; 2.3 One sample; 2.4 Related samples; 2.5 Independent samples; 2.6 Factorial designs; 2.7 Observational study designs; 2.7.1 Cross-sectional design; 2.7.2 Case-control design; 2.7.3 Longitudinal studies; 2.7.4 Surveys; 2.8 Sampling; 2.9 Reliability and validity; 2.10 Summary; References; 3 Probability - 'Probability ... So True in General'; 3.1 Aims; 3.2 What is probability?; 3.3 Frequentist probability; 3.4 Bayesian probability

3.5 The likelihood approach3.6 Summary; References; 4 Summarising Data - 'Transforming Data into Information'; 4.1 Aims; 4.2 Why summarise?; 4.3 Summarising data numerically - descriptive statistics; 4.3.1 Measures of central location; 4.3.2 Measures of dispersion; 4.4 Summarising data graphically; 4.5 Graphs for summarising group data; 4.5.1 The bar graph; 4.5.2 The error plot; 4.5.3 The box-and-whisker plot; 4.5.4 Comparison of graphs for group data; 4.5.5 A little discussion on error bars; 4.6 Graphs for displaying relationships between variables; 4.6.1 The scatter diagram or plot

4.6.2 The line graph4.7 Displaying complex (multidimensional) data; 4.8 Displaying proportions or percentages; 4.8.1 The pie chart; 4.8.2 Tabulation; 4.9 Summary; References; 5 Statistical Power - '. . . Find out the Cause of this Effect'; 5.1 Aims; 5.2 Power; 5.3 From doormats to aortic valves; 5.4 More on the normal distribution; 5.4.1 The central limit theorem; 5.5 How is power useful?; 5.5.1 Calculating the power; 5.5.2 Calculating the sample size; 5.6 The problem with p values; 5.7 Confidence intervals and power; 5.8 When to stop collecting data

5.9 Likelihood versus null hypothesis testing5.10 Summary; References; 6 Comparing Groups using t-Tests and ANOVA - 'To Compare is not to Prove'; 6.1 Aims; 6.2 Are men taller than women?; 6.3 The central limit theorem revisited; 6.4 Student's t-test; 6.4.1 Calculation of the pooled standard deviation; 6.4.2 Calculation of the t statistic; 6.4.3 Tables and tails; 6.5 Assumptions of the t-test; 6.6 Dependent t-test; 6.7 What type of data can be tested using t-tests?; 6.8 Data transformations; 6.9 Proof is not the answer; 6.10 The problem of multiple testing

6.11 Comparing multiple means - the principles of analysis of variance

Sommario/riassunto

To form a strong grounding in human-related sciences it is essential for students to grasp the fundamental concepts of statistical analysis, rather than simply learning to use statistical software. Although the software is useful, it does not arm a student with the skills necessary to formulate the experimental design and analysis of a research project in later years of study or indeed, if working in research.   This textbook deftly covers a topic that many students find difficult. With an engaging and accessible style it provides the necessary background and tools for



students to use statist

2.

Record Nr.

UNINA9910254627203321

Autore

Haywood Raphaëlle D

Titolo

Radial-velocity Searches for Planets Around Active Stars / / by Raphaëlle D. Haywood

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016

ISBN

3-319-41273-6

Edizione

[1st ed. 2016.]

Descrizione fisica

1 online resource (XV, 140 p. 60 illus., 57 illus. in color.)

Collana

Springer Theses, Recognizing Outstanding Ph.D. Research, , 2190-5053

Disciplina

629.4113

Soggetti

Astronomy

Astronomy—Observations

Astrophysics

Space sciences

Exobiology

Astronomy, Observations and Techniques

Astrophysics and Astroparticles

Space Sciences (including Extraterrestrial Physics, Space Exploration and Astronautics)

Astrobiology

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

"Doctoral thesis accepted by the University of St. Andrews, UK."

Nota di bibliografia

Includes bibliographical references at the end of each chapters and index.

Nota di contenuto

Introduction: the Hunt for Extra-solar Planets -- A Toolkit to Detect Planets Around Active Stars -- Application to Observations of Planet-hosting Stars -- An Exploration into the Radial-velocity Variability of the Sun -- Conclusion.

Sommario/riassunto

This thesis develops new and powerful methods for identifying planetary signals in the presence of “noise” generated by stellar activity, and explores the physical origin of stellar intrinsic variability, using unique observations of the Sun seen as a star. In particular, it



establishes that the intrinsic stellar radial-velocity variations mainly arise from suppression of photospheric convection by magnetic fields. With the advent of powerful telescopes and instruments we are now on the verge of discovering real Earth twins in orbit around other stars. The intrinsic variability of the host stars themselves, however, currently remains the main obstacle to determining the masses of such small planets. The methods developed here combine Gaussian-process regression for modeling the correlated signals arising from evolving active regions on a rotating star, and Bayesian model selection methods for distinguishing genuine planetary signals from false positives produced by stellar magnetic activity. The findings of this thesis represent a significant step towards determining the masses of potentially habitable planets orbiting Sun-like stars. .