Math 300 , Spring 2004, Day 13, M, March 1 After classHit reload to get most current version

In class closed book Quiz Monday day 16: all the "Named" distributions.  Practice Sheet (don't hand in).
Geometric and Neg. Binomial Day 12

Start here Wednesday
Poisson distribution

X =Number of "hits" in a fixed interval of space or time (interval can be area or volume)
   = Number of successes in Binomial, with p small and n large.
Lambda = np = expected number of hits/successes in the whole interval (whole n trials).
|___|_x_|___|___|__x|___|x__|___| 8 trials, 3 hits

Handout: Tables & stuff.  Will go over the proof of the binomial~Poisson connection (handout, or p. 64) in class.

  Note the table gives the probability < x, just like a Normal table.

HW Geometric: Read Ash pp. 51-2. Also Finite Geom. / Geometric Series, p. 36. HW Day 12

Read : Poisson
Ash sec. 2-5, also p. 36, the exponential series.

HW will be assigned Wed: Poisson Ash p. 68, the non-Review problems:
  #2
  #3 (Poisson and binomial. compare)
  4, 5, 6, 7
A. Suppose that on the average a certain store gets 5 customers per hour.  Consider now a two-hour period.
  a) What is lambda for the 2-hour period?
  b) What is the probability that the store will get 12 or fewer customers in the two hour period?  (Use the table)
  c) What is the probability that the store will get 13 or more customers in the two hour period?
  d) What is the probability that the store will get exactly 13 customers in the two hour period?

B.  Use Siegrist Applet, Poisson Experiment.  Experiment: Number of arrivals in [0,t],  r is the expected number per unit time.
Lambda is shown as "mean", bottom of  N column.

Do the Store of problem A, 2 hour period, 5 customers per hour. (t=2, r=5)  Run a few simulations.  Read off Distribution Table (right of graph) , Distribution column, the probability of 13 arrivals.
Compare with your answer to (Ad).  It should match, within .001.
Run r up and down, note the skewness of the distribution for small r, and the approach to normal for larger r.

The Geometric measured the waiting time till the first Binomial success.
There is a parallel variable measuring the waiting time till the first Poisson hit.  It's called the Exponential, but it's a continuous R.V. so we'll see it later.
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