This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.
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.
- 5 stars63.47%
- 4 stars24.42%
- 3 stars7.76%
- 2 stars2.05%
- 1 star2.28%
I like really course content but it would be better to add exlaination for quiz (especially when initial answer is wrong, now student can only see explainations when answer question right)
Brian Caffo is the best statistics teacher I have ever had. I like how he breaks down things and he covers the ways to think about statistics far beyond any course I have taken.
This course is phenomenally well developed with great curriculum and materials for building astrong base to enter into statistics with a strong base of knowledge.
I think this a good course for practicing concepts, but the quizzes are not quite appropriate for a beginner's course.
关于 Advanced Statistics for Data Science 专项课程
Fundamental concepts in probability, statistics and linear models are primary building blocks for data science work. Learners aspiring to become biostatisticians and data scientists will benefit from the foundational knowledge being offered in this specialization. It will enable the learner to understand the behind-the-scenes mechanism of key modeling tools in data science, like least squares and linear regression.