Tutorial for Probability and statistics 2 (NMAI073)

TA: Robert Šámal

Rules for credit

Coordinates

Thu 17:20, S7

Homeworks

to be submitted in the Postal Owl. Let me know if you did not receive enrollment token.
You may submit a handwritten solution (scanned/nicely photographed), a computer prepared pdf file, or you can write the solution in the page using a combination of markdown and tex.
Partial solutions are fine (for a partial credit).
Discussing homework with other students is allowed. However, you should then write the solution yourself (and understand what you are doing).

Problems discussed each week

• Tutorial 1
  A homework is posted in the owl. (It is problem 7 from the list, but in a better formulation.)
• Tutorial 2 (corrected version, there were typos in the printed version)
  Jupyter notebook for problems 4 & 5 (updated with stuff done during the tutorial)
  
  A homework is posted in the owl. (It is problem 8 from the list, to be solved both theoretically and on computer.)
• On Oct 20 there is no in-person tutorial. You may use the time to review statistics from the first semester using the following python notebooks:
  Interval estimates using Normal distribution -- look at it and check it with the formulas from class. Try to modify this for the case when sigma is not known to you: that is, the function CI should only get as parameters x and alpha. (Hint: the right way to get sample standard deviation is statistics.stdev(x). There are other similar functions, but some of them do not apply the Bessel correction.
  Point estimates of uniform distribution -- look at it and think about what is says about the two estimates. Try to find a better estimate. If you still have time and energy, repeat for another distribution (e.g., geometrical distribution).
  hypothesis testing -- coming soon
• Tutorial 3
  
• Tutorial 4
• Tutorial 5
  Homework: problem number~6, see the Owl.
• Tutorial 6
  Python notebook for Bernoulli processes
  Python notebook for Poisson processes
  
• Tutorial 7
  Next week we will write a credit test!
• Credit test (version A)
  Credit test (version B)
  
• Tutorial 8
  
• Tutorial 9
  Python notebook
  
• Tutorial 10