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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Université DukeÀ propos de ce cours
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Niveau débutant
Approx. 10Â heures pour terminer
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Sous-titres : Arabe, Français, Portugais (européen), Italien, Vietnamien, Coréen, Allemand, Russe, Anglais, Espagnol
Compétences que vous acquerrez
- Statistics
- Linear Regression
- R Programming
- Regression Analysis
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Niveau débutant
Approx. 10Â heures pour terminer
Anglais
Sous-titres : Arabe, Français, Portugais (européen), Italien, Vietnamien, Coréen, Allemand, Russe, Anglais, Espagnol
Offert par
Université 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.
Programme de cours : ce que vous apprendrez dans ce cours
22Â minutes pour terminer
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!
22Â minutes pour terminer
1 vidéo (Total 2 min), 2 lectures
2Â heures pour terminer
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.
2Â heures pour terminer
8 vidéos (Total 47 min), 3 lectures, 2 quiz
3Â heures pour terminer
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!
3Â heures pour terminer
3 vidéos (Total 24 min), 5 lectures, 3 quiz
5Â heures pour terminer
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. There is also a final project included in this week. You will use the data set provided to complete and report on a data analysis question. Please read the project instructions to complete this self-assessment.
5Â heures pour terminer
7 vidéos (Total 57 min), 6 lectures, 3 quiz
Avis
- 5 stars80,12Â %
- 4 stars16,05Â %
- 3 stars3Â %
- 2 stars0,25Â %
- 1 star0,56Â %
Meilleurs avis pour LINEAR REGRESSION AND MODELING
par AB27 nov. 2017
Great course! I've already taken a similar stats course using SPSS and this course was an excellent refresher, while increasing my familiarity with R.
par JM12 janv. 2017
This course was good. However, compared to the other courses in the specialisation had less content. I would have liked to have videos on logistic regression as well.
par EB25 févr. 2017
Good, but a little "smaller" than the Inferential statistics course (which is very complete). I would have liked to also learn Logistics regression, which I now have to learn elsewhere.
par MM13 déc. 2020
I learn a lot. It added more lessons beyond my graduate school. Especially that the course is based on R, this course is very helpful for my journey towards using R.
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