Probabilities and some elementary statistics make a cornerstone for modern language technology. For some of you, but not all, this will be well known knowledge from earlier studies. But for they who are not familiar with the concepts, or need a brush up, we will give one (or more) tutorials on the basics that everybody has to know. The content of the tutorial(s) will be considered part of the curriculum/syllabus and a precondition for solving some of the exam questions.
Tutorial 1: Tuesday 17 Sept, 1015 sem.rom Postscript
(I.e. this replaces the normal lab sessions, but we change room)
We will consider the basic theory, as well as how some of this can be computed with scipy.stats.
Tutorial 2: Tuesday 15 Oct, 1015 sem.rom Postscript
(I.e. this replaces the normal lab sessions, but we change room)
This time we will definitely take a look at scipy.stats and we will consider probaility distributions: bernoulli, binomial and normal (gaussian) distribution (cf. Ch. 3 in OpenIntro.)
Readings
OpenIntro (3. ed.) (In the 4th ed. add one to the chapter numbers)
- Ch. 2, "Probability", sec. 2.1-2.4
- Ch. 3, "Distributions of random variables":
- Sec. 3.3.1 Bernoulli distribution
- Sec. 3.4.1 Binomial distribution