ECON 2500 Lecture Notes - Fair Coin, Sample Space, Randomness

• School: York University
• Department: Economics
• Course: ECON 2500
• Professor: all

Document Summary

Econ 2500 winter 2011 xianghong li. Chapter 4 probability: the study of randomness feb 15. Deterministic event: e. g. my car won"t run without gas. Random events: the outcome is uncertain before it occurs, there is a regular pattern for possible outcomes in a large number of repetitions. (not true for chaotic or haphazard events, such as earthquake). Sample space s of a random phenomenon: the set of all possible outcomes: e. g. tossing a coin once s = {h, t, e. g. Do you favour mandatory retirement s = {y, n} Event: a set of outcomes of a random phenomenon. Event space: e. g. toss a fair coin twice: Toss a fair coin four times: using a tree structure to exhaust all possible outcomes, define the outcomes as number of heads, sample space, comment: the sample space depends on how we define individual outcome. Assign a probability to each individual outcome.