Notably we will be covering the statistics bucket from the diagram above and trying to make it as intuitive and maths-lite as possible.



My background is in big pharma, academia (a PhD from Oxford's Physical and Theoretical Chemistry department) and "data science for social good" industries across southern and eastern Africa.



This series of posts aims to introduce and quickly develop some core concepts in data science and data analysis, with a specific focus on areas that I feel are overlooked or treated briefly in other materials. Therefore, these posts will suit data scientists looking to brush up on statistical theory, data analysts looking for thorough training materials, and data managers who want to ask better questions from their data and their staff.


I guess you came to this post by searching similar kind of issues in any of the search engine and hope that this resolved your problem. If you find this tips useful, just drop a line below and share the link to others and who knows they might find it useful too.

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