Segment 8. Some Standard Distributions

From Computational Statistics (CSE383M and CS395T)
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(Don't worry, what you see statically below is not the beginning of the segment. Press the play button to start at the beginning.)

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The direct YouTube link is http://youtu.be/EDYDC7iNGTg Links to the slides: PDF file or PowerPoint file

Problems

To Calculate

1. In Segment 6 (slide 8) we used the improper prior <math>1/r</math>. Show that this is just a limiting case of a (completely proper) Lognormal prior.

2. Prove that <math>{\rm Gamma}(\alpha,\beta)</math> has a single mode at <math>(\alpha-1)/\beta</math> when <math>\alpha \ge 1</math>.

3. Show that the limiting case of the Student distribution as <math>\nu\rightarrow\infty</math> is the Normal distribution.

To Think About

1. Suppose you have an algorithm that can compute a CDF, <math>P(x)</math>. How would you design an algorithm to compute its inverse (see slide 9) <math>x(P)</math>?

2. The lifetime t of a radioactive nucleus (say Uranium 238) is distributed as the Exponential distribution. Do you know why? (Hint: What is the distribution of an Exponential<math>(\beta)</math> random variable conditioned on its being greater than some given value?)

Class Activity

problem statement: ClassActivity20130204.pdf

data file for class activity: events20130204.txt

Jeff's Python code