Tools for data analysis
- Autores
- Pérez Lloret, Santiago; Enet, Alejandro; Gonzalez Aleman, Gabriela
- Año de publicación
- 2024
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Fil: Pérez Lloret, Santiago. Pontificia Universidad Católica Argentina. Observatorio de Salud Publica; Argentina
Fil: Pérez Lloret, Santiago. Consejo de Investigaciones Científicas y Técnicas; Argentina.
Fil: Pérez Lloret, Santiago. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Fisiología; Argentina
Fil: Enet, Alejandro. Pontificia Universidad Católica Argentina. Observatorio de Salud Publica; Argentina
Fil: Gonzalez Aleman, Gabriela. Pontificia Universidad Católica Argentina. Facultad de Psicología y Psicopedagogía,; Argentina
What are statistics Good for in human research studies? Studies conducted on human beings may have different objectives and designs, but they all share some common principles. 1 We outline these principles as a cycle, shown in Figure 1. The first step is to obtain a sample from a population. A population is a group of human beings sharing one or more characteristics. In medical research, researchers usually define populations following a disease or a condition. Obtaining the sample is called “sampling”. 2 Researchers will then discuss the study with the potential participants. They will be part of the study sample if they accept to participate and fulfill all inclusion and exclusion criteria. Investigators will perform a series of procedures and assessments and may apply an intervention to the sample of participants. For example, a treatment may be used, and its effects on Parkinson’s Disease motor symptoms may be recorded. Notably, study results only represent the effects of the intervention on the sample of participants. However, researchers are generally interested in “extrapolating” these results to the target population. The “statistical inference” procedure allows for performing such extrapolations. 3 Statistics is the science of collecting, analyzing, and describing data to conclude a particular phenomenon based on a relatively limited sample material. 3 It employs mathematical and probabilistic tools to develop methods and models for data analysis... - Fuente
- Movement Disorders Clinical Practice. 2024
- Materia
-
ESTADISTICAS
ANALISIS DE DATOS - Nivel de accesibilidad
- acceso embargado
- Condiciones de uso
- Repositorio
- Institución
- Pontificia Universidad Católica Argentina
- OAI Identificador
- oai:ucacris:123456789/19079
Ver los metadatos del registro completo
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Tools for data analysisPérez Lloret, SantiagoEnet, AlejandroGonzalez Aleman, GabrielaESTADISTICASANALISIS DE DATOSFil: Pérez Lloret, Santiago. Pontificia Universidad Católica Argentina. Observatorio de Salud Publica; ArgentinaFil: Pérez Lloret, Santiago. Consejo de Investigaciones Científicas y Técnicas; Argentina.Fil: Pérez Lloret, Santiago. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Fisiología; ArgentinaFil: Enet, Alejandro. Pontificia Universidad Católica Argentina. Observatorio de Salud Publica; ArgentinaFil: Gonzalez Aleman, Gabriela. Pontificia Universidad Católica Argentina. Facultad de Psicología y Psicopedagogía,; ArgentinaWhat are statistics Good for in human research studies? Studies conducted on human beings may have different objectives and designs, but they all share some common principles. 1 We outline these principles as a cycle, shown in Figure 1. The first step is to obtain a sample from a population. A population is a group of human beings sharing one or more characteristics. In medical research, researchers usually define populations following a disease or a condition. Obtaining the sample is called “sampling”. 2 Researchers will then discuss the study with the potential participants. They will be part of the study sample if they accept to participate and fulfill all inclusion and exclusion criteria. Investigators will perform a series of procedures and assessments and may apply an intervention to the sample of participants. For example, a treatment may be used, and its effects on Parkinson’s Disease motor symptoms may be recorded. Notably, study results only represent the effects of the intervention on the sample of participants. However, researchers are generally interested in “extrapolating” these results to the target population. The “statistical inference” procedure allows for performing such extrapolations. 3 Statistics is the science of collecting, analyzing, and describing data to conclude a particular phenomenon based on a relatively limited sample material. 3 It employs mathematical and probabilistic tools to develop methods and models for data analysis...Wileyinfo:eu-repo/date/embargoEnd/2025-06-112024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://repositorio.uca.edu.ar/handle/123456789/190792330-1619 (online)10.1002/mdc3.1409238863258Movement Disorders Clinical Practice. 2024reponame:Repositorio Institucional (UCA)instname:Pontificia Universidad Católica Argentinaenginfo:eu-repo/semantics/embargoedAccess2025-07-03T11:00:03Zoai:ucacris:123456789/19079instacron:UCAInstitucionalhttps://repositorio.uca.edu.ar/Universidad privadaNo correspondehttps://repositorio.uca.edu.ar/oaiclaudia_fernandez@uca.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:25852025-07-03 11:00:03.868Repositorio Institucional (UCA) - Pontificia Universidad Católica Argentinafalse |
dc.title.none.fl_str_mv |
Tools for data analysis |
title |
Tools for data analysis |
spellingShingle |
Tools for data analysis Pérez Lloret, Santiago ESTADISTICAS ANALISIS DE DATOS |
title_short |
Tools for data analysis |
title_full |
Tools for data analysis |
title_fullStr |
Tools for data analysis |
title_full_unstemmed |
Tools for data analysis |
title_sort |
Tools for data analysis |
dc.creator.none.fl_str_mv |
Pérez Lloret, Santiago Enet, Alejandro Gonzalez Aleman, Gabriela |
author |
Pérez Lloret, Santiago |
author_facet |
Pérez Lloret, Santiago Enet, Alejandro Gonzalez Aleman, Gabriela |
author_role |
author |
author2 |
Enet, Alejandro Gonzalez Aleman, Gabriela |
author2_role |
author author |
dc.subject.none.fl_str_mv |
ESTADISTICAS ANALISIS DE DATOS |
topic |
ESTADISTICAS ANALISIS DE DATOS |
dc.description.none.fl_txt_mv |
Fil: Pérez Lloret, Santiago. Pontificia Universidad Católica Argentina. Observatorio de Salud Publica; Argentina Fil: Pérez Lloret, Santiago. Consejo de Investigaciones Científicas y Técnicas; Argentina. Fil: Pérez Lloret, Santiago. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Fisiología; Argentina Fil: Enet, Alejandro. Pontificia Universidad Católica Argentina. Observatorio de Salud Publica; Argentina Fil: Gonzalez Aleman, Gabriela. Pontificia Universidad Católica Argentina. Facultad de Psicología y Psicopedagogía,; Argentina What are statistics Good for in human research studies? Studies conducted on human beings may have different objectives and designs, but they all share some common principles. 1 We outline these principles as a cycle, shown in Figure 1. The first step is to obtain a sample from a population. A population is a group of human beings sharing one or more characteristics. In medical research, researchers usually define populations following a disease or a condition. Obtaining the sample is called “sampling”. 2 Researchers will then discuss the study with the potential participants. They will be part of the study sample if they accept to participate and fulfill all inclusion and exclusion criteria. Investigators will perform a series of procedures and assessments and may apply an intervention to the sample of participants. For example, a treatment may be used, and its effects on Parkinson’s Disease motor symptoms may be recorded. Notably, study results only represent the effects of the intervention on the sample of participants. However, researchers are generally interested in “extrapolating” these results to the target population. The “statistical inference” procedure allows for performing such extrapolations. 3 Statistics is the science of collecting, analyzing, and describing data to conclude a particular phenomenon based on a relatively limited sample material. 3 It employs mathematical and probabilistic tools to develop methods and models for data analysis... |
description |
Fil: Pérez Lloret, Santiago. Pontificia Universidad Católica Argentina. Observatorio de Salud Publica; Argentina |
publishDate |
2024 |
dc.date.none.fl_str_mv |
2024 info:eu-repo/date/embargoEnd/2025-06-11 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
https://repositorio.uca.edu.ar/handle/123456789/19079 2330-1619 (online) 10.1002/mdc3.14092 38863258 |
url |
https://repositorio.uca.edu.ar/handle/123456789/19079 |
identifier_str_mv |
2330-1619 (online) 10.1002/mdc3.14092 38863258 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Wiley |
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Wiley |
dc.source.none.fl_str_mv |
Movement Disorders Clinical Practice. 2024 reponame:Repositorio Institucional (UCA) instname:Pontificia Universidad Católica Argentina |
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Repositorio Institucional (UCA) |
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Repositorio Institucional (UCA) |
instname_str |
Pontificia Universidad Católica Argentina |
repository.name.fl_str_mv |
Repositorio Institucional (UCA) - Pontificia Universidad Católica Argentina |
repository.mail.fl_str_mv |
claudia_fernandez@uca.edu.ar |
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1836638375595999232 |
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13.22299 |