Acerca de este curso: 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.
Creada por: Duke University
Enseñado por: Mine Çetinkaya-Rundel, Associate Professor of the Practice
Department of Statistical Science
| Información básica | Curso 3 de 5 en Statistics with R Specialization |
| Nivel | Principiante |
| Compromiso | 4 weeks of study, 5-7 hours/week |
| Idioma | English |
| Cómo aprobar | Aprueba todas las tareas calificadas para completar el curso. |
| Calificaciones del usuario |
Programa
SEMANA 1
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, 2 lecturas
- Reading: About Statistics with R Specialization
- Reading: More about Linear Regression and Modeling
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, 3 lecturas, 1 cuestionario de práctica
- Reading: Lesson Learning Objectives
- Vídeo: Correlation
- Vídeo: Residuals
- Vídeo: Least Squares Line
- Reading: Lesson Learning Objectives
- Vídeo: Prediction and Extrapolation
- Vídeo: Conditions for Linear Regression
- Vídeo: R Squared
- Vídeo: Regression with Categorical Explanatory Variables
- Reading: Week 1 Suggested Readings and Practice
- Practice Quiz: Week 1 Practice Quiz
Calificado: Week 1 Quiz
SEMANA 2
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, 3 lecturas, 1 cuestionario de práctica
- Reading: Lesson Learning Objectives
- Vídeo: Inference for Linear Regression
- Vídeo: Variability Partitioning
- Reading: Week 2 Suggested Readings and Exercises
- Practice Quiz: Week 2 Practice Quiz
- Reading: Instructions for Week 1 & 2 Lab
Calificado: Week 2 Quiz
Calificado: Week 1 & 2 Lab
SEMANA 3
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, 4 lecturas, 1 cuestionario de práctica
- Reading: Lesson Learning Objectives
- Vídeo: Multiple Predictors
- Vídeo: Adjusted R Squared
- Vídeo: Collinearity and Parsimony
- Reading: Lesson Learning Objectives
- Vídeo: Inference for MLR
- Vídeo: Model Selection
- Vídeo: Diagnostics for MLR
- Reading: Week 3 Suggested Readings and Exercises
- Practice Quiz: Week 3 Practice Quiz
- Reading: Instructions for Week 3 Lab
Calificado: Week 3 Quiz
Calificado: Week 3 Lab
SEMANA 4
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 lectura
- Reading: Project Files and Rubric
Calificado: Data Analysis Project
Preguntas Frecuentes
Cómo funciona
Coursework
Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.
Help from Your Peers
Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.
Certificates
Earn official recognition for your work, and share your success with friends, colleagues, and employers.
Creadores
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.
Tarifa
| Comprar curso | |
|---|---|
| Accede a los materiales del curso | Disponible |
| Accede a los materiales con calificación | Disponible |
| Recibe una calificación final | Disponible |
| Obtén un Certificado de curso para compartir | Disponible |
Calificaciones y revisiones
Brilliant Course
How I loved this course! Elegantly taught and lots of learning :)
Great Lesson!
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Simple and easy way to understand statistics.