Informações sobre o curso
4.7
767 ratings
137 reviews
This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractiveness of a professor and their student evaluation scores? Can we predict the test score for a child based on certain characteristics of his or her mother? In this course, you will learn the fundamental theory behind linear regression and, through data examples, learn to fit, examine, and utilize regression models to examine relationships between multiple variables, using the free statistical software R and RStudio....
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Prazos flexíveis

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Beginner Level

Nível iniciante

Clock

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

Aprox. 14 horas restantes
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English

Legendas: English

Habilidades que você terá

StatisticsLinear RegressionR ProgrammingRegression Analysis
Globe

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Beginner Level

Nível iniciante

Clock

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

Aprox. 14 horas restantes
Comment Dots

English

Legendas: English

Programa - O que você aprenderá com este curso

1

Seção
Clock
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!...
Reading
1 vídeo (Total de 2 min), 2 leituras
Reading2 leituras
About Statistics with R Specialization10min
More about Linear Regression and Modeling10min
Clock
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. ...
Reading
8 vídeos (Total de 47 min), 3 leituras, 2 testes
Video8 videos
Correlation9min
Residuals1min
Least Squares Line11min
Prediction and Extrapolation3min
Conditions for Linear Regression10min
R Squared4min
Regression with Categorical Explanatory Variables5min
Reading3 leituras
Lesson Learning Objectives10min
Lesson Learning Objectives10min
Week 1 Suggested Readings and Practice10min
Quiz2 exercícios práticos
Week 1 Practice Quiz8min
Week 1 Quiz18min

2

Seção
Clock
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!...
Reading
3 vídeos (Total de 24 min), 3 leituras, 3 testes
Video3 videos
Inference for Linear Regression11min
Variability Partitioning5min
Reading3 leituras
Lesson Learning Objectives10min
Week 2 Suggested Readings and Exercises10min
Instructions for Week 1 & 2 Lab10min
Quiz3 exercícios práticos
Week 2 Practice Quiz6min
Week 2 Quiz16min
Week 1 & 2 Lab20min

3

Seção
Clock
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!...
Reading
7 vídeos (Total de 57 min), 4 leituras, 3 testes
Video7 videos
Multiple Predictors11min
Adjusted R Squared10min
Collinearity and Parsimony3min
Inference for MLR11min
Model Selection11min
Diagnostics for MLR7min
Reading4 leituras
Lesson Learning Objectives10min
Lesson Learning Objectives10min
Week 3 Suggested Readings and Exercises10min
Instructions for Week 3 Lab10min
Quiz3 exercícios práticos
Week 3 Practice Quiz16min
Week 3 Quiz20min
Week 3 Lab20min

4

Seção
Clock
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. ...
Reading
1 leitura, 1 teste
Reading1 leituras
Project Files and Rubric10min
4.7
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17%

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Briefcase

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Melhores avaliações

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 PSSep 15th 2017

fantastic course on linear regression, concepts are well explained followed by quiz and practical exercises.\n\nthough you need to complete the prior courses to understand this.

Instrutores

Mine Çetinkaya-Rundel

Associate Professor of the Practice
Department of Statistical Science

Sobre Duke University

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

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • 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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