Harvard's course is the best course to take if you want to gain a comprehensive understanding of introductory probability and statistics.
If you want to dive deeper into the foundations of probability, MIT 6.012 is a nice complement.
If you haven't had a math course in a long time or think the Harvard or MIT courses are too hard, Khan Academy's modules are a great introduction as well.
MIT 18.650 is more suitable for people who already had an introduction to probability and statistics.
Overall the best introduction course to probability and statistics. The combination of lectures, problem sets and the free textbook will give you a comprehensive overview from the ground up.
This course goes through a lot of the probability theory topics of the above course in a bit more depth and provides more step-by-step guidance, e.g. by reviewing set theory.
The most approachable course on the topic. In typical Khan Academy fashion, it equips the learner with a broad overview of the topic by providing simple explanations and insightful examples.
This course is suitable for anyone who already has some basic understanding of probability and statistics. It goes through applications of statistics such as parametric inference, principal component analysis and generalized linear models.
Doesn't cover a lot of probability theory, but goes through statistics topics such as summarizing data, inference and linear regression in a very approachable manner. Includes chapter videos and coding labs.