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.
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I knew a lot about probability before starting this course, but I didn't know much of anything about frequentist statistics. This course helped me understand some tricky concepts.
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.
Very concise, well-presented course. This was my second time taking it as a refresher. Prof. Caffo does a great job presenting the materials. However, prepare to be challenged.
Great course, though a little difficult in parts, particularly the first week. Worth working through though for a better understanding of probability and statistics.
關於 Advanced Statistics for Data Science 專項課程
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.