STAT 2000 Lecture 10: February 8

• School: University of Georgia
• Department: Statistics
• Course: STAT 2000
• Professor: Dunlap

Document Summary

Probability: allows us to make the jump from describing a sample to drawing conclusions or inferences about the population: random and chance. As number of trials increases, the variability decreases. Random behavior is unpredictable in short run. (cid:4666)(cid:4667)= # (cid:3042)(cid:3033) (cid:3042)(cid:3048)(cid:3047)(cid:3042)(cid:3040)(cid:3032)(cid:3046) (cid:3041) (cid:3047)(cid:3042)(cid:3047)(cid:3039) # (cid:3042)(cid:3033) (cid:3042)(cid:3048)(cid:3047)(cid:3042)(cid:3040)(cid:3032)(cid:3046) Sample space: a listing of all possible outcomes i. e. rolling a dice: the sample space= 1, 2, 3, 4, 5, 6. Event: subset of sample space; events denoted by a or b i. e. let a= roll a 5; let b=roll an even # 3 important properties of probabilities: 1. The sum of all probable possibilities= 1: 3. The complement rule i. e. 52% of americans have played the lottery. 1-0. 52=0. 48; so, the answer would be 48% Notation: probability of a given b , where b is the condition, p(a/b) Example 8: rolling a die: suppose event a is rolling a 6 and event b is rolling an even number.