Statistics is a discipline in which datasets about a given sample are analyzed to generalize information about the broader population that the sample represents. Relatedly, probability is the study of chance.

Step #1: Learn itStep #2: Apply itStep #3: Stay up-to-date

Access the following free resources from across the web. Note that Bootstrap Ed does not own any of the resources featured on this page. 

Probability

  • Charles Grinstead and J. Laurie Snell – Introduction to Probability
  • MIT – Introduction to Probability (6-012), Lecturer: John Tsitsikli
    • 20 lectures split into shorter parts, approximately 5-15 minutes each
    • Playlist
  • Harvard – Probability (STAT-E 110), Lecturer: Joe Blitzstein
    • 35 lectures, approximately 45 minutes each
    • Playlist
  • UCLA – Probability for Life Science (Math 3C), Lecturer: Herbert Enderton
    • 28 lectures, approximately 45 minutes each
    • Playlist
  • UC Irvine – Introduction to Probability and Statistics (Math 131A), Lecturer: Michael Cranston
    • 16 lectures, approximately 105 minutes each
    • Playlist

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Statistics

  • AllPsych.com – Statistics Primer
  • MIT – Fundamentals of Statistics (18.650), Lecturer: Philippe Rigollet
    • 24 lecturers, approximately 75 minutes each
    • Playlist
  • Khan Academy – Statistics
    • 68 lectures, approximately 5-15 minutes each
    • Playlist

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R Resources

Datasets

  • UC Irvine – Machine Learning Repository
  • Analytics Vidhya – 24 Ultimate Data Science Projects To Boost Your Knowledge and Skills (& can be accessed freely)

Complete the following exercise to apply your newly acquired knowledge.

  • ANALYZE (4-6 pages double spaced)
    • Analyze a dataset using a statistical method covered in the materials presented here. Describe the dataset, the question(s) you are attempting to answer, your methods, and findings.

Engage with the field on an ongoing basis. Note that Bootstrap Ed does not own any of the resources featured on this page. 

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Related topics: Calculus, Data Science

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