Acerca de este Curso
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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

22 minutos para completar

About Linear Regression and Modeling

This short module introduces basics about Coursera specializations and courses in general, this specialization: Statistics with R, and this course: Linear Regression and Modeling. Please take several minutes to browse them through. Thanks for joining us in this course!

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

Linear Regression

In this week we’ll introduce linear regression. Many of you may be familiar with regression from reading the news, where graphs with straight lines are overlaid on scatterplots. Linear models can be used for prediction or to evaluate whether there is a linear relationship between two numerical variables.

8 videos (Total 47 minutos), 3 readings, 2 quizzes
8 videos
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
2 horas para completar

More about Linear Regression

Welcome to week 2! In this week, we will look at outliers, inference in linear regression and variability partitioning. Please use this week to strengthen your understanding on linear regression. Don't forget to post your questions, concerns and suggestions in the discussion forum!

3 videos (Total 24 minutos), 5 readings, 3 quizzes
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
3 horas para completar

Multiple Regression

In this week, we’ll explore multiple regression, which allows us to model numerical response variables using multiple predictors (numerical and categorical). We will also cover inference for multiple linear regression, model selection, and model diagnostics. Hope you enjoy!

7 videos (Total 57 minutos), 5 readings, 3 quizzes
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
2 horas para completar

Final Project

In this week you will use the data set provided to complete and report on a data analysis question. Please read the background information, review the report template (downloaded from the link in Lesson Project Information), and then complete the peer review assignment.

1 reading, 1 quiz
1 lectura
Project Files and Rubric10m
168 revisionesChevron Right


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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.



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 del 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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