Desenvolvido por:   Johns Hopkins University

  • Brian Caffo, PhD

    Ministrado 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

Perguntas frequentes
Como funciona
Trabalho
Trabalho

Cada curso é como um livro didático interativo, com vídeos pré-gravados, testes e projetos.

Ajuda dos seus colegas
Ajuda dos seus colegas

Conecte-se com milhares de outros aprendizes, debata ideias, discuta sobre os materiais do curso e obtenha ajuda para dominar conceitos.

Certificados
Certificados

Obtenha reconhecimento oficial pelo seu trabalho e compartilhe seu sucesso com amigos, colegas e empregadores.

Desenvolvedores
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.
Classificações e avaliações
Avaliado em 4 de 5 decorrente de 26 avaliações

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.



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