### STU33009: Statistical Methods for Computer Science 2019-20

Lectures: Weds 3-5pm LB01
Tutorials: Weds 1-2pm LG12
Lecturer: Doug Leith
Tutorial Assistants: Goksu Yamac

The module is a first course in probability and statistics that only assumes basic mathematical (algebra, sets) and programming (we'll use matlab) knowledge. The aim is to take students to the point where they have the foundation needed for understanding machine learning techniques (and so for a follow on module on machine learning or to read an introductory book), performance analysis of computer systems etc.

The module is divided into four parts (each roughly three weeks long) and the topics covered in each part are summarised here.

Assessment is 70% final exam, 20% mid-term exam (held directly after reading week) and 10% marked weekly questions.

 Week 1 Counting. Slides. Permutations. Slides. Matlab Lab handout. Test questions. Solutions. More test questions. Solution checker. Solutions. Weekly Questions. Solution checker Week 2 Axioms of Probability. Slides. Algebra revision. Slides. Conditional Probability and Bayes Theorem. Slides. Test questions. Solutions. More test questions. Solution checker. Solutions. Weekly Questions. Solution checker Week 3 Independence. Slides. Review of material to date (for study in own time). Slides. Random Variables. Slides. Test questions. Solutions. More test questions. Solution checker. Solutions. Weekly Questions. Solution checker Week 4 Bernoulli and Binomial RVs. Slides. Mean and Variance. Slides. Test questions. Solutions. More test questions. Solution checker. Solutions. Weekly Questions. Solution checker Week 5 Correlation and Conditional Expectation. Slides. Review (for study in own time). Slides. Inequalities. Slides. Test questions. Solutions. More test questions. Solution checker. Solutions. Weekly Questions. Solution checker Week 6 Sample mean, Weak law of large numbers and CLT. Slides. Confidence Intervals. Slides. Test questions. Solutions. More test questions. Solution checker. Solutions. Week 7 Week 8 No Lecture Weekly Questions. Week 9 Logistic Regression. Slides. Test questions. Solutions. Weekly Questions. Week 10 Into to Linear Regression. Slides Continuous random variables. Slides. Test questions. Solutions. More test questions. Solution checker. Solutions. Even more test questions. Solution checker. Solutions. Weekly Questions. Week 11 Probabilistic Interpretation Of Linear Regression. Slides. Test questions. Solutions. More test questions. Solution checker. Solutions. Week 12