ADM 2303 Lecture Notes - Lecture 5: Poisson Distribution, Probability Distribution

• School: University of Ottawa
• Department: Administration
• Course: ADM 2303
• Professor: David Wright

Document Summary

Poisson distribution: used to model # of arrivals of events. Average # of events per unit of time is . Events are independent of each other, (occurrence of 1 event does not influence chances of another event) Probability that an event occurs in a given unit of time is the same for all times. Customers arriving for service per unit time at: drive through banking. Occurrence of earthquakes, automobile accidents, meteorites hitting. = expected # of successes in a segment t e = base of natural # system (2. 71828) x = # success (cid:449)here space stations, per unit time. Binomial calculates p(x) where x < n. # of defective products in a sample of 10. # of pho(cid:374)e calls per (cid:373)i(cid:374)ute o(cid:374) mother"s da(cid:455) Poisson example: a fast food restaurant has customers arriving for drive-through service at a rate of 60 per hour. Nb scale the arrival rate to the time interval of interest.