Informações sobre o curso
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Prazos flexíveis

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Nível iniciante

Aprox. 14 horas para completar

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


Legendas: Inglês

Habilidades que você terá

StatisticsLinear RegressionR ProgrammingRegression Analysis

100% online

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível iniciante

Aprox. 14 horas para completar

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


Legendas: Inglês

Programa - O que você aprenderá com este curso

22 minutos para concluir

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 vídeo ((Total 2 mín.)), 2 leituras
2 leituras
About Statistics with R Specialization10min
More about Linear Regression and Modeling10min
2 horas para concluir

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 vídeos ((Total 47 mín.)), 3 leituras, 2 testes
8 videos
Least Squares Line11min
Prediction and Extrapolation3min
Conditions for Linear Regression10min
R Squared4min
Regression with Categorical Explanatory Variables5min
3 leituras
Lesson Learning Objectives10min
Lesson Learning Objectives10min
Week 1 Suggested Readings and Practice10min
2 exercícios práticos
Week 1 Practice Quiz8min
Week 1 Quiz18min
2 horas para concluir

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 vídeos ((Total 24 mín.)), 5 leituras, 3 testes
3 videos
Inference for Linear Regression11min
Variability Partitioning5min
5 leituras
Lesson Learning Objectives10min
Week 2 Suggested Readings and Exercises10min
About Lab Choices10min
Week 1 & 2 Lab Instructions (RStudio)10min
Week 1 & 2 Lab Instructions (RStudio Cloud)10min
3 exercícios práticos
Week 2 Practice Quiz6min
Week 2 Quiz16min
Week 1 & 2 Lab20min
3 horas para concluir

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 vídeos ((Total 57 mín.)), 5 leituras, 3 testes
7 videos
Multiple Predictors11min
Adjusted R Squared10min
Collinearity and Parsimony3min
Inference for MLR11min
Model Selection11min
Diagnostics for MLR7min
5 leituras
Lesson Learning Objectives10min
Lesson Learning Objectives10min
Week 3 Suggested Readings and Exercises10min
Week 3 Lab Instructions (RStudio)10min
Week 3 Lab Instructions (RStudio Cloud)10min
3 exercícios práticos
Week 3 Practice Quiz16min
Week 3 Quiz20min
Week 3 Lab20min
2 horas para concluir

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 leitura, 1 teste
1 leituras
Project Files and Rubric10min
168 avaliaçõesChevron Right


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Principais avaliações do 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

Sobre Universidade 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....

Sobre o Programa de cursos integrados 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

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.

  • 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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