2S: Statistics

2S: Statistics

Autumn 2016

Tuesdays 4pm-5pm LAW LT-1

Thursdays 9am-10am ARTS Main LT

Examples class: Tuesday 5pm-6pm LAW LT-1 in weeks 3,5,7,9, 11

Instructor

Will Perkins

w.f.perkins@bham.ac.uk

Office: Watson 211

Office Hours: Tuesdays, 3:00pm - 4:00pm, Thursdays 10:00am-11:00am, or by appointment

Course Information

Main Topics of the Course:

  1. The statistical method
    • Descriptive statistics
    • Statistical inference
    • Statistical significance
    • Modern statistics: machine learning and algorithmic statistics
    • Pitfalls of statistics:
  2. Probability theory
    • Independence and conditioning
    • Random variables
    • Expectation and variance
  3. Limit theorems
    • Convergence of random variables
    • The Law of Large Numbers
    • The Central Limit Theorem

Course materials

All course materials (lecture notes, problems sheets, review sheets, solution sheets, discussion forum) are on the University of Birmingham Canvas site.

Schedule
  • Sep 27 Aims and methods of statistics

  • Sep 29 Descriptive statistics

  • Oct 4 Probabilistic models for data

  • Oct 6 Outcomes, events, and probability

  • Oct 11Inclusion, exclusion

    Examples class

  • Oct 13Independence and conditioning

  • Oct 18Discrete random variables

  • Oct 20 Political polling

  • Oct 25 Continuous random variables

    Examples class

  • Oct 27Random vectors

  • Nov 1 Class Test 1

  • Nov 3Expectation

  • Nov 8 Variance

    Examples class

  • Nov 10Covariance matrices

  • Nov 15Second moment method

  • Nov 17Law of Large Numbers

  • Nov 22Convergence of random variables

    Examples class

  • Nov 24 Central Limit Theorem

  • Nov 29Properties of the Normal distribution

  • Dec 1Class Test 2

  • Dec 6 Random walks

    Examples class

  • Dec 8 Statistics and prediction