Acerca de este Curso
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100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

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Nivel principiante

Aprox. 14 horas para completar

Sugerido: 4 weeks of study, 5-7 hours/week...

Inglés (English)

Subtítulos: Inglés (English)

Habilidades que obtendrás

StatisticsLinear RegressionR ProgrammingRegression Analysis

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel principiante

Aprox. 14 horas para completar

Sugerido: 4 weeks of study, 5-7 hours/week...

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
22 minutos para completar

About Linear Regression and Modeling

1 videos (Total 2 minutos), 2 lecturas
2 lecturas
About Statistics with R Specialization10m
More about Linear Regression and Modeling10m
2 horas para completar

Linear Regression

8 videos (Total 47 minutos), 3 lecturas, 2 cuestionarios
8 videos
Correlation9m
Residuals1m
Least Squares Line11m
Prediction and Extrapolation3m
Conditions for Linear Regression10m
R Squared4m
Regression with Categorical Explanatory Variables5m
3 lecturas
Lesson Learning Objectives10m
Lesson Learning Objectives10m
Week 1 Suggested Readings and Practice10m
2 ejercicios de práctica
Week 1 Practice Quiz8m
Week 1 Quiz18m
Semana
2
2 horas para completar

More about Linear Regression

3 videos (Total 24 minutos), 5 lecturas, 3 cuestionarios
3 videos
Inference for Linear Regression11m
Variability Partitioning5m
5 lecturas
Lesson Learning Objectives10m
Week 2 Suggested Readings and Exercises10m
About Lab Choices10m
Week 1 & 2 Lab Instructions (RStudio)10m
Week 1 & 2 Lab Instructions (RStudio Cloud)10m
3 ejercicios de práctica
Week 2 Practice Quiz6m
Week 2 Quiz16m
Week 1 & 2 Lab20m
Semana
3
3 horas para completar

Multiple Regression

7 videos (Total 57 minutos), 5 lecturas, 3 cuestionarios
7 videos
Multiple Predictors11m
Adjusted R Squared10m
Collinearity and Parsimony3m
Inference for MLR11m
Model Selection11m
Diagnostics for MLR7m
5 lecturas
Lesson Learning Objectives10m
Lesson Learning Objectives10m
Week 3 Suggested Readings and Exercises10m
Week 3 Lab Instructions (RStudio)10m
Week 3 Lab Instructions (RStudio Cloud)10m
3 ejercicios de práctica
Week 3 Practice Quiz16m
Week 3 Quiz20m
Week 3 Lab20m
Semana
4
2 horas para completar

Final Project

1 lectura, 1 cuestionario
1 lecturas
Project Files and Rubric10m
4.7
179 revisionesChevron Right

33%

comenzó una nueva carrera después de completar estos cursos

45%

consiguió un beneficio tangible en su carrera profesional gracias a este curso

12%

consiguió un aumento de sueldo o ascenso

Principales revisiones sobre Linear Regression and Modeling

por PKMay 24th 2017

Very good course taught by Dr. Mine who is as always a very good teacher. The videos are very eloquent and easy to understand. Highly recommend it if you are looking for a basic refresher course.

por RZMay 25th 2019

I feel I'm running out of complement words for this course series. In conclusion, clear teaching, helpful project, and knowledgeable classmates that I can learn from through final project.

Instructores

Avatar

Mine Çetinkaya-Rundel

Associate Professor of the Practice
Department of Statistical Science

Acerca de 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....

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. You will produce a portfolio of data analysis projects from the Specialization that demonstrates mastery of statistical data analysis from exploratory analysis to inference to modeling, suitable for applying for statistical analysis or data scientist positions....
Statistics with R

Preguntas Frecuentes

  • Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.

  • 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.

  • 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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