Youtube.com is the second most accessed website in the world (surpassed only by its parent, google.com). It has a whopping 1 billion unique views a month. [1, 2] It is a force to be reckoned with. In the video sharing platform, there are many brilliant and hard-working content creators producing high-quality and free educational videos that students and academics alike can enjoy. I made a survey on Youtube content that could be useful for those interested in learning Statistics, and I listed and categorized them below.

Truth be told, this post is a glorified Google search in many respects. In any case, I had intended for a long time to gather this information as to facilitate the often laborious task of finding pertinent resources for learning statistical science in a non-static format (i.e., videos) that is easily accessible, high-quality, instructive and free.

Another motivation had to do with my teaching obligations. In this fall, I will teach a graduate course in Stats with R. To this end, I considered becoming a content creator myself, as to allow students to access the course’s content from the convenience of their homes. In this process, I found some excellent statistical courses on Youtube. Some were really useful in terms of their organization, others in terms of content, interesting explanations, pedagogical skills, availability of materials, etc. Altogether, searching for resources was a very instructive experience, whose fruits should be shared.

Importantly, in this process, I learned that youtube is not short of ‘introductory course on ___.’ Not of Statistics, Probability or R, anyways. Which is a good thing. And often, you even see these three together. Also in abundance, are courses on the ABC’s of probability theory, classical statistics (i.e., up to ANOVA, ANCOVA), and on basics of applied statistics (e.g., Econometrics, Biostatistics, and Machine Learning). Indeed, Machine Learning (mostly through Data Science) is really well represented on Youtube.

Due to the sheer amount of channels, I organized them into three broad categories: use of R as statistical software, use of other statistical software, and lecture format only. I also listed each channel’s content/topic, whether authors provided slides, code, additional materials online (with links), and relevant remarks.

1. LEARNING STATISTICS WITH R