This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The concepts and techniques in this course will serve as building blocks for the inference and modeling courses in the Specialization.
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Programa Especializado - Statistics with RUniversidad DukeAcerca de este Curso
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Resultados profesionales del estudiante
33%
comenzó una nueva carrera después de completar estos cursos
30%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
11%
consiguió un aumento de sueldo o ascenso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 1 de 5 en
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel principiante
Aprox. 14 horas para completar
Inglés (English)
Subtítulos: Inglés (English), Coreano
Habilidades que obtendrás
StatisticsR ProgrammingRstudioExploratory Data Analysis
Resultados profesionales del estudiante
33%
comenzó una nueva carrera después de completar estos cursos
30%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
11%
consiguió un aumento de sueldo o ascenso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 1 de 5 en
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel principiante
Aprox. 14 horas para completar
Inglés (English)
Subtítulos: Inglés (English), Coreano
ofrecido por
Universidad Duke
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
Programa - Qué aprenderás en este curso
12 minutos para completar
About Introduction to Probability and Data
This course introduces you to sampling and exploring data, as well as basic probability theory. You will examine various types of sampling methods and discuss how such methods can impact the utility of a data analysis. The concepts in this module will serve as building blocks for our later courses.Each lesson comes with a set of learning objectives that will be covered in a series of short videos. Supplementary readings and practice problems will also be suggested from OpenIntro Statistics, 3rd Edition, https://leanpub.com/openintro-statistics/, (a free online introductory statistics textbook, that I co-authored). There will be weekly quizzes designed to assess your learning and mastery of the material covered that week in the videos. In addition, each week will also feature a lab assignment, in which you will use R to apply what you are learning to real data. There will also be a data analysis project designed to enable you to answer research questions of your own choosing. Since this is a Coursera course, you are welcome to participate as much or as little as you’d like, though I hope that you will begin by participating fully. One of the most rewarding aspects of a Coursera course is participation in forum discussions about the course materials. Please take advantage of other students' feedback and insight and contribute your own perspective where you see fit to do so. You can also check out the resource page (https://www.coursera.org/learn/probability-intro/resources/crMc4) listing useful resources for this course. Thank you for joining the Introduction to Probability and Data community! Say hello in the Discussion Forums. We are looking forward to your participation in the course.
12 minutos para completar
1 video (Total 2 minutos), 1 lectura
1 video
1 lectura
More about Introduction to Probability and Data10m
2 horas para completar
Introduction to Data
Welcome to Introduction to Probability and Data! I hope you are just as excited about this course as I am! In the next five weeks, we will learn about designing studies, explore data via numerical summaries and visualizations, and learn about rules of probability and commonly used probability distributions. If you have any questions, feel free to post them on this module's forum (https://www.coursera.org/learn/probability-intro/module/rQ9Al/discussions?sort=lastActivityAtDesc&page=1) and discuss with your peers! To get started, view the learning objectives (https://www.coursera.org/learn/probability-intro/supplement/rooeY/lesson-learning-objectives) of Lesson 1 in this module.
2 horas para completar
6 videos (Total 28 minutos), 2 lecturas, 2 cuestionarios
6 videos
Data Basics5m
Observational Studies & Experiments4m
Sampling and sources of bias8m
Experimental Design2m
(Spotlight) Random Sample Assignment3m
2 lecturas
Lesson Learning Objectives10m
Suggested Readings and Practice10m
2 ejercicios de práctica
Week 1 Practice Quiz30m
Week 1 Quiz30m
1 hora para completar
Introduction to Data Project
To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.
1 hora para completar
2 lecturas
2 lecturas
About Lab Choices (Read Before Selection)10m
Week 1 Lab Instructions (RStudio)10m
1 ejercicio de práctica
Week 1 Lab: Introduction to R and RStudio30m
2 horas para completar
Exploratory Data Analysis and Introduction to Inference
Welcome to Week 2 of Introduction to Probability and Data! Hope you enjoyed materials from Week 1. This week we will delve into numerical and categorical data in more depth, and introduce inference.
2 horas para completar
7 videos (Total 46 minutos), 3 lecturas, 2 cuestionarios
7 videos
Measures of Center4m
Measures of Spread6m
Robust Statistics1m
Transforming Data3m
Exploring Categorical Variables8m
Introduction to Inference12m
3 lecturas
Lesson Learning Objectives10m
Lesson Learning Objectives10m
Suggested Readings and Practice10m
2 ejercicios de práctica
Week 2 Practice Quiz30m
Week 2 Quiz30m
1 hora para completar
Exploratory Data Analysis and Introduction to Inference Project
To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.
1 hora para completar
2 lecturas
2 lecturas
Week 2 Lab Instructions (RStudio)10m
Week 2 Lab Instructions (RStudio Cloud)10m
1 ejercicio de práctica
Week 2 Lab: Introduction to Data30m
3 horas para completar
Introduction to Probability
Welcome to Week 3 of Introduction to Probability and Data! Last week we explored numerical and categorical data. This week we will discuss probability, conditional probability, the Bayes’ theorem, and provide a light introduction to Bayesian inference. Thank you for your enthusiasm and participation, and have a great week! I’m looking forward to working with you on the rest of this course.
3 horas para completar
9 videos (Total 82 minutos), 3 lecturas, 2 cuestionarios
9 videos
Disjoint Events + General Addition Rule9m
Independence9m
Probability Examples9m
(Spotlight) Disjoint vs. Independent2m
Conditional Probability12m
Probability Trees10m
Bayesian Inference14m
Examples of Bayesian Inference7m
3 lecturas
Lesson Learning Objectives10m
Lesson Learning Objectives10m
Suggested Readings and Practice10m
2 ejercicios de práctica
Week 3 Practice Quiz30m
Week 3 Quiz30m
1 hora para completar
Introduction to Probability Project
To complete this assignment you will use R and RStudio installed on your local computer or through RStudio Cloud.
1 hora para completar
2 lecturas
2 lecturas
Week 3 Lab Instructions (RStudio)10m
Week 3 Lab Instructions (RStudio Cloud)10m
1 ejercicio de práctica
Week 3 Lab: Probability30m
3 horas para completar
Probability Distributions
Great work so far! Welcome to Week 4 -- the last content week of Introduction to Probability and Data! This week we will introduce two probability distributions: the normal and the binomial distributions in particular. As usual, you can evaluate your knowledge in this week's quiz. There will be no labs for this week. Please don't hesitate to post any questions, discussions and related topics on this week's forum (https://www.coursera.org/learn/probability-intro/module/VdVNg/discussions?sort=lastActivityAtDesc&page=1).
3 horas para completar
6 videos (Total 67 minutos), 4 lecturas, 2 cuestionarios
6 videos
Evaluating the Normal Distribution2m
Working with the Normal Distribution5m
Binomial Distribution17m
Normal Approximation to Binomial14m
Working with the Binomial Distribution9m
4 lecturas
Lesson Learning Objectives10m
Lesson Learning Objectives10m
Suggested Readings and Practice10m
Data Analysis Project Example10m
2 ejercicios de práctica
Week 4 Practice Quiz30m
Week 4 Quiz30m
Reseñas
Principales reseñas sobre INTRODUCTION TO PROBABILITY AND DATA WITH R
por AA23 de ene. de 2018
This course literally taught me a lot, the concepts were beautifully explained but the way it was delivered and overall exercises and the difficulty of problems made it more challenging and enjoying.
por AA9 de jun. de 2017
A good introductory course to data analysis, statistics and the R programming language. Recommended to people who are new to data analysis and also those who are experienced and could use a refresh.
por BB3 de sep. de 2019
Very clearly explained and the pace is awesome! I really enjoy each deadline and l can already see how it is impacting my day to day work and life. I ook forward to completing the course! Thank you.
por HD30 de mar. de 2018
The tutor makes it really simple. The given examples really helped to understand the concepts and apply it to a wide range of problems. Thank you for this. Wish I could complete the assignments too.
Acerca de Programa especializado: Statistics with R
In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
El acceso a las clases y las asignaciones depende del tipo de inscripción que tengas. Si tomas un curso en modo de oyente, verás la mayoría de los materiales del curso en forma gratuita. Para acceder a asignaciones calificadas y obtener un certificado, deberás comprar la experiencia de Certificado, ya sea durante o después de participar como oyente. Si no ves la opción de oyente:
- es posible que el curso no ofrezca la opción de participar como oyente. En cambio, puedes intentar con una Prueba gratis o postularte para recibir ayuda económica.
- Es posible que el curso ofrezca la opción 'Curso completo, sin certificado'. Esta opción te permite ver todos los materiales del curso, enviar las evaluaciones requeridas y obtener una calificación final. También significa que no podrás comprar una experiencia de Certificado.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
Is financial aid available?
Sí, Coursera ofrece ayuda económica a los estudiantes que no pueden pagar la tarifa. Solicítala haciendo clic en el enlace de Ayuda económica que está debajo del botón “Inscribirse” a la izquierda. Se te pedirá que completes una solicitud. Recibirás una notificación en caso de que se apruebe. Deberás completar este paso para cada uno de los cursos que forman parte del Programa especializado, incluido el proyecto final. Obtén más información.
Will I receive a transcript from Duke University for completing this course?
No. Completion of a Coursera course does not earn you academic credit from Duke; therefore, Duke is not able to provide you with a university transcript. However, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
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