Applied Statistics - Week 4

The following is a description of what we will go through during this week of the course. The chapter references and computer exercises are considered read, understood, and solved by the beginning of the following class, where I'll shortly go through the exercise solution.

General notes, links, and comments:

:

Monday:
The main theme of this week will be Hypothesis testing, and we will start with an exercise gently introducing the subject.

Reading:

Barlow, chapter 8 on hypothesis testing.
Lecture(s):

Hypothesis Testing
Computer Exercise(s):

Weldon's Dices: WeldonsDices.py, and an example solution: WeldonsDices_solution.py

Tuesday:
In addition to the ChiSquare test, there are several other tests, some simple (one/two sample tests) and some more conceptually challenging (Kolmogorov and Wald-Wolfowitz runs test). I will re-iterate on these tests, and the exercise of the day will focus exactly on different tests.
Exceptionally, today's lecture will be on Confidence Intervals, which is a related subject, but also one we will not have any exercise associated (as it is fairly general).

Reading:

Barlow, chapter 7.2
Lecture(s):

Confidence Intervals And Limits
Computer Exercise(s):

Hypothesis testing: HypothesisTests.py

Friday:
The day will focus on calibration, which is a subtle subject, yet fairly straight forward, once you get the hang of the idea. The associated exercise is inspired by typical data analysis work.

Reading:

No reading - logic and reason suffices.
Lecture(s):

Calibration
Computer Exercise(s):

Calibration.py and data file

Extra: NBI Coffee Usage: CoffeeUsage.py

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Last updated: 9th of December 2015.