Creada por:   Johns Hopkins University

  • Brian Caffo, PhD

    Enseñado por:    Brian Caffo, PhD, Professor, Biostatistics

    Bloomberg School of Public Health
Language
English
How To PassPass all graded assignments to complete the course.
User Ratings
4.0 stars
Average User Rating 4.0See what learners said
Programa

Preguntas Frecuentes
Cómo funciona
Trabajo del curso
Trabajo del curso

Cada curso es como un libro de texto interactivo, con videos pregrabados, cuestionarios y proyectos.

Ayuda de tus compañeros
Ayuda de tus compañeros

Conéctate con miles de estudiantes y debate ideas y materiales del curso, y obtén ayuda para dominar los conceptos.

Certificados
Certificados

Obtén reconocimiento oficial por tu trabajo y comparte tu éxito con amigos, compañeros y empleadores.

Creadores
Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Calificaciones y revisiones
Calificado 4 de 5 26 calificaciones

Thankful that a course like this exists, as most MOOCs are quite basic. And thanks to Coursera for running the courses even though attendance seems to be low (darn, that pesky calculus pre-requisite). Lecture quality is varied--some quite good (such as the lectures in Boot Camp I) and others seem like he hadn't looked at his notes for a long time. It's great to hear a stats professor talk about the strengths and weaknesses of many approaches. It complements a mathematical statistics book quite well. It would have been nice to have had some problems that were more challenging. Overall, while the Johns Hopkins Data Science MOOCs are pretty good, they are a bit more basic than what's available through MIT and Stanford.

This course should be part of the Data Science specialization. Actually, you can supplement the Statistical Inference course with these two Boot camp courses really well!

A great revision of statistics, very rigorous and thorough cover of all distributions and hypothesis tests.