lecture 8—probability and statistics (ch. 3) friday january 25 th quiz on chapter 2 classical and...
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Lecture 8—Probability and Statistics Lecture 8—Probability and Statistics (Ch. 3)(Ch. 3)
Friday January 25Friday January 25thth
•Quiz on Chapter 2
•Classical and statistical probability
•The axioms of probability theory
•Independent events
•Counting events
Reading: Reading: All of chapter 3 (pages 52 - 64)All of chapter 3 (pages 52 - 64)Homework 2 due TODAYHomework 2 due TODAY***Homework 3 due Fri. Feb. 1st*******Homework 3 due Fri. Feb. 1st****Assigned problems, Assigned problems, Ch. 3Ch. 3: 8, 10, 16, 18, : 8, 10, 16, 18,
2020Homework assignments available on Homework assignments available on
web pageweb pageExam 1: two weeks from today, Fri. Feb. 8th (in Exam 1: two weeks from today, Fri. Feb. 8th (in class)class)
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ClassicalClassicalThermodynamicsThermodynamics
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Classical and statistical probabilityClassical and statistical probability
Classical probability:
•Consider all possible outcomes (simple events) of a process (e.g. a game).
•Assign an equal probability to each outcome.
Let W = number of possible outcomes (ways)Assign probability pi to the ith outcome
1 1& 1i i
i
p p WW W
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Classical and statistical probabilityClassical and statistical probability
Classical probability:
•Consider all possible outcomes (simple events) of a process (e.g. a game).
•Assign an equal probability to each outcome.
Examples:
Coin toss:Coin toss:
WW = 2 = 2 ppii = 1/2 = 1/2
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Classical and statistical probabilityClassical and statistical probability
Classical probability:
•Consider all possible outcomes (simple events) of a process (e.g. a game).
•Assign an equal probability to each outcome.
Examples:
Rolling a dice:Rolling a dice:
WW = 6 = 6 ppii = 1/6 = 1/6
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Classical and statistical probabilityClassical and statistical probability
Classical probability:
•Consider all possible outcomes (simple events) of a process (e.g. a game).
•Assign an equal probability to each outcome.
Examples:
Drawing a card:Drawing a card:
WW = 52 = 52 ppii = 1/52 = 1/52
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Classical and statistical probabilityClassical and statistical probability
Classical probability:
•Consider all possible outcomes (simple events) of a process (e.g. a game).
•Assign an equal probability to each outcome.
Examples:
FL lottery jackpot:FL lottery jackpot:
WW = 20M = 20M ppii = 1/20M = 1/20M
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Classical and statistical probabilityClassical and statistical probability
Statistical probability:
•Probability determined by measurement (experiment).
•Measure frequency of occurrence.
•Not all outcomes necessarily have equal probability.•Make Make N N trialstrials
•Suppose Suppose iithth outcome occurs outcome occurs nnii times times
lim ii N
np
N
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Classical and statistical probabilityClassical and statistical probability
Statistical probability:
•Probability determined by measurement (experiment).
•Measure frequency of occurrence.
•Not all outcomes necessarily have equal probability.Example: lim 0.312i
iN
np
N
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Classical and statistical probabilityClassical and statistical probability
Statistical probability:
•Probability determined by measurement (experiment).
•Measure frequency of occurrence.
•Not all outcomes necessarily have equal probability.More examples:
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Classical and statistical probabilityClassical and statistical probability
Statistical probability:
•Probability determined by measurement (experiment).
•Measure frequency of occurrence.
•Not all outcomes necessarily have equal probability.More examples:
![Page 12: Lecture 8—Probability and Statistics (Ch. 3) Friday January 25 th Quiz on Chapter 2 Classical and statistical probability The axioms of probability theory](https://reader035.vdocument.in/reader035/viewer/2022081515/56649e7b5503460f94b7bc2e/html5/thumbnails/12.jpg)
0 1 2 3 4 5
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
N 1 0.510 0.15100 0.041000 0.013210000 0.00356100000 0.00145
log( )
log(N)
log log
0.516
a N b
a
Statistical fluctuationsStatistical fluctuations
1/ 2N
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The axioms of probability theoryThe axioms of probability theory
1. pi ≥ 0, i.e. pi is positive or zero
2. pi ≤ 1, i.e. pi is less than or equal to 1
3. For mutually exclusive events, the probabilities for compound events, i and j, add
i ji jp p p
• Compound events, (Compound events, (ii + + jj): this means either event ): this means either event ii occurs, or event occurs, or event jj occurs, or both. occurs, or both.
• Mutually exclusive: events Mutually exclusive: events ii and and jj are said to be mutually exclusive are said to be mutually exclusive if it is impossible for both outcomes (events) to occur in a single if it is impossible for both outcomes (events) to occur in a single trial.trial.
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The axioms of probability theoryThe axioms of probability theory
1. pi ≥ 0, i.e. pi is positive or zero
2. pi ≤ 1, i.e. pi is less than or equal to 1
3. For mutually exclusive events, the probabilities for compound events, i and j, add
• In general, for In general, for rr mutually exclusive events, the probability that one mutually exclusive events, the probability that one of the of the rr events occurs is given by: events occurs is given by:
1 2 ........ rp p p p
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Independent eventsIndependent events
Example:What is the probability of What is the probability of rolling two sixes?rolling two sixes?
Classical probabilities:Classical probabilities:
16 6p
Two sixes:Two sixes:
1 1 16,6 6 6 36p
•Truly independent events always satisfy this property.
•In general, probability of occurrence of r independent events is:1 2 ........ rp p p p