4.6
stars
26 ratings

Roger D. Peng, PhD +1 more instructor

1,514 already enrolled

Offered By

Gestión del análisis de datos

Johns Hopkins University

About this Course

6,567 recent views

This one-week course describes the process of analyzing data and how to manage that process. We describe the iterative nature of data analysis and the role of stating a sharp question, exploratory data analysis, inference, formal statistical modeling, interpretation, and communication. In addition, we will describe how to direct analytic activities within a team and to drive the data analysis process towards coherent and useful results. 
This is a focused course designed to rapidly get you up to speed on the process of data analysis and how it can be managed. Our goal was to make this as convenient as possible for you without sacrificing any essential content. We've left the technical information aside so that you can focus on managing your team and moving it forward.

After completing this course you will know how to….

1. Describe the basic data analysis iteration
2. Identify different types of questions and translate them to specific datasets
3. Describe different types of data pulls
4. Explore datasets to determine if data are appropriate for a given question
5. Direct model building efforts in common data analyses
6. Interpret the results from common data analyses
7. Integrate statistical findings to form coherent data analysis presentations

Commitment: 1 week of study, 4-6 hours

Course cover image by fdecomite. Creative Commons BY https://flic.kr/p/4HjmvD

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Approx. 9 hours to complete

Spanish

What you will learn

Differentiate between various types of data pulls
Describe the basic data analysis iteration
Explore datasets to determine if data is appropriate for a project
Use statistical findings to create convincing data analysis presentations

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Approx. 9 hours to complete

Spanish

Instructors

Instructor rating

4.87/5 (8 Ratings)

Roger D. Peng, PhD

Associate Professor, Biostatistics

Bloomberg School of Public Health

1,489,241 Learners

37 Courses

Jeff Leek, PhD

Associate Professor, Biostatistics

Bloomberg School of Public Health

1,526,613 Learners

32 Courses

Offered by

Johns Hopkins University

Syllabus - What you will learn from this course

Week

Week 1

9 hours to complete

Gestión del análisis de datos

¡Te damos la bienvenida a Gestión del análisis de datos! Este curso consiste en un módulo diseñado para realizarse en una semana. El curso funciona mejor si avanzas con el material en el orden en el que se presenta. Cada clase cuenta con videos y material de lectura que aportan información adicional a la clase. Me entusiasma tenerte en la clase y espero recibir tus contribuciones para la comunidad de estudiantes. Si tienes preguntas sobre el contenido del curso, publícalas en el foro para obtener ayuda de otras personas de la comunidad del curso. Si tienes problemas técnicos con la plataforma de Coursera, visita el Centro de ayuda para estudiantes. ¡Buena suerte en el inicio del curso y espero que lo disfrutes!

9 hours to complete

19 videos (Total 144 min), 17 readings, 7 quizzes

19 videos

Sobre qué trata el curso2m

Iteración del análisis de datos8m

Etapas del análisis de datos1m

Seis tipos de preguntas6m

Características de una buena pregunta6m

Objetivos y expectativas del análisis exploratorio de datos11m

Cómo usar los modelos estadísticos para explorar tus datos (parte 1)13m

Cómo usar los modelos estadísticos para explorar tus datos (parte 2)5m

Análisis exploratorio de datos: cuándo detenerse6m

Cómo hacer inferencias a partir de los datos: introducción5m

Las poblaciones vienen de muchas formas4m

Inferencia: qué puede salir mal7m

Marco general8m

Análisis de asociación10m

Análisis de predicción10m

Inferencia vs. predicción12m

Cómo interpretar los resultados10m

Comunicación de rutina en el análisis de datos6m

Cómo realizar una presentación de análisis de datos5m

17 readings

Encuesta previa al curso10m

Libro de texto del curso: "The Art of Data Science" (El arte de la ciencia de datos)10m

"Conversations on Data Science" (Conversaciones sobre la ciencia de datos)10m

"Data Science as Art" (Ciencia de datos como arte)10m

Epiciclos del análisis10m

Seis tipos de preguntas10m

Características de una buena pregunta10m

Lista de verificación del AED10m

Evaluación de una distribución10m

Evaluación de relaciones lineales10m

Análisis exploratorio de datos: ¿cuándo nos detenemos?10m

Factores que afectan la calidad de la inferencia10m

Comentario sobre las poblaciones10m

Inferencia vs. predicción10m

Cómo interpretar los resultados10m

Comunicación de rutina10m

Encuesta posterior al curso10m

7 practice exercises

Iteración del análisis de datos30m

Planteamiento y refinamiento de la pregunta30m

Análisis exploratorio de datos30m

Inferencia30m

Modelado formal, Inferencia vs. predicción30m

Interpretación30m

Comunicación30m

Reviews

4.6

5 reviews

5 stars
61.53%
4 stars
34.61%
3 stars
3.84%

TOP REVIEWS FROM GESTIÓN DEL ANÁLISIS DE DATOS

by VQAug 23, 2022

La importancia de un buen análisis de dato y lo compleja que pude ser si no se empieza bien.

by JLApr 6, 2022

Excelent course, that personal reasons I was need finished in thre days, the abstract information, i will need reviewed

View all reviews

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Gestión del análisis de datos

Gestión del análisis de datos

About this Course

What you will learn