Course - Probability MT22

Created: October 17, 2022 | Updated: October 21, 2025 | About these notes | View in context | Study these flashcards

---

An introduction to probability theory, starting from the axioms of a probability space and ending at the weak law of large numbers and Chebyshev’s inequality. A lot more than was covered in Stats at A-Level.

There were some really fun problem sheet questions in this course, like this one from Sheet 1: “Celia the centipede has 100 feet, 100 socks, and 100 shoes. How many orders can she choose from to put on her socks and shoes? (She must put a sock on foot $i$ before putting a shoe on foot $i$.)”.

• Course Webpage
• Lecture Notes
• Some of the lectures from this course are available on YouTube.
• Other courses this term: [[Courses MT22]]^U

Notes

• [[Notes - Probability MT22, Probability spaces]]^U
• [[Notes - Probability MT22, Basic definitions]]^U
• [[Notes - Probability MT22, Partition theorem]]^U
• [[Notes - Probability MT22, Bayes’ theorem]]^U
• [[Notes - Probability MT22, Random variables]]^U
• [[Notes - Probability MT22, Distributions]]^U
• [[Notes - Probability MT22, Expectation]]^U
• [[Notes - Probability MT22, Variance and covariance]]^U
• [[Notes - Probability MT22, Recurrence relations]]^U
• [[Notes - Probability MT22, Probability generating functions]]^U
• [[Notes - Probability MT22, Random sums theorem]]^U
• [[Notes - Probability MT22, Moments]]^U
• [[Notes - Probability MT22, Branching processes]]^U
• [[Notes - Probability MT22, Random samples]]^U
• [[Notes - Probability MT22, Weak law of large numbers]]^U
• [[Notes - Probability MT22, Markov’s inequality]]^U
• [[Notes - Probability MT22, Chebyshev’s inequality]]^U
• [[Notes - Probability MT22, Misc]]^U

Lectures

• [[Lecture - Probability MT22, I]]^U
• [[Lecture - Probability MT22, II]]^U
• [[Lecture - Probability MT22, III]]^U
• [[Lecture - Probability MT22, IV]]^U
• [[Lecture - Probability MT22, V]]^U
• [[Lecture - Probability MT22, VI]]^U
• [[Lecture - Probability MT22, VII]]^U
• [[Lecture - Probability MT22, VIII]]^U
• [[Lecture - Probability MT22, IX]]^U
• [[Lecture - Probability MT22, X]]^U
• [[Lecture - Probability MT22, XI]]^U
• [[Lecture - Probability MT22, XII]]^U
• [[Lecture - Probability MT22, XIII]]^U
• [[Lecture - Probability MT22, XIV]]^U
• [[Lecture - Probability MT22, XV]]^U
• [[Lecture - Probability MT22, XVI]]^U

Problem Sheets

• Sheet 1
• Sheet 2
• Sheet 3
• Sheet 4
• Sheet 5
• Sheet 6
• Sheet 7
• Sheet 8

---

Related posts

• [[Notes - Probability MT22, Basic definitions]]^U

  (incoming)
• [[Notes - Probability MT22, Markov's inequality]]^U

  (incoming)
• [[Notes - Probability MT22, Probability generating functions]]^U

  (incoming)
• [[Notes - Probability MT22, Probability spaces]]^U

  (incoming)
• [[Lecture - Machine Learning MT23, II]]^U

  (incoming)
• [[Notes - Probability MT22, Random variables]]^U

  (incoming)
• [[Notes - Probability MT22, Expectation]]^U

  (incoming)
• [[University Notes]]^U

  (incoming)
• [[Notes - Probability MT22, Chebyshev's inequality]]^U

  (incoming)
• [[Notes - Probability MT22, Partition theorem]]^U

  (incoming)
• [[Notes - Probability MT22, Random samples]]^U

  (incoming)
• [[Course - Uncertainty in Deep Learning MT25]]^U

  (incoming)
• [[Notes - Probability MT22, Weak law of large numbers]]^U

  (incoming)
• [[Prelims]]^U

  (incoming)
• [[Notes - Uncertainty in Deep Learning MT25, Probability reference]]^U

  (incoming)
• [[Notes - Probability MT22, Misc]]^U

  (incoming)
• [[Notes - Probability MT22, Variance and covariance]]^U

  (incoming)
• [[Notes - Probability MT22, Bayes' theorem]]^U

  (incoming)
• [[Notes - Probability MT22, Branching processes]]^U

  (incoming)
• [[Notes - Probability MT22, Moments]]^U

  (incoming)
• [[Courses MT22]]^U

  (incoming)
• [[Notes - Probability MT22, Random sums theorem]]^U

  (incoming)
• [[Notes - Probability MT22, Recurrence relations]]^U

  (incoming)
• [[Lecture - Probability MT22, II]]^U

  (sim: 0.528)
• [[Lecture - Probability MT22, IV]]^U

  (sim: 0.515)
• [[Lecture - Probability MT22, XII]]^U

  (sim: 0.504)
• [[Course - Probability MT25]]^U

  (sim: 0.499)