Chapter 7 Econ Behav

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1
outcome space
a set of possible outcomes usually written in brackets
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Example of outcome space
For a coin flip {H,T}
For flipping a coin twice {HH,HT,TH,TT}
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Outcome
A subset of the outcome space
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Example of outcome
Outcome of heads in a coin flip {H}
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Probability Function
Is denoted as Pr().
It is a function that maps outcomes to probabilities.
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Pr(A) = X
A is the outcome. It is the input to the probability function.
X is the probability. It is the output of the probability functno
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Example of probability. Pr(Heads)=
0.5
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Probabilities range from
0(will not happen with certainty) to 1(will happen with certainty)
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The probability of rolling a seven with a six-sided die is
ZERO!
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Everything Rule
The probability of the entire outcome set is 1
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Example of everything rule
Rolling 1-6 with a six-sided die is 1
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Not Rule
The probability of anything but outcome A, which we call Pr(Not A), =1-Pr(A)
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Probability of Not Rule Example
Probability of a American roulette wheel is red.
Pr(Red) = 9/19, so the probability of any other outcome.
Pr(Not Red), is equal to 1-9/19, or 10/19
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Equal probability
If all outcomes have equal probability, then the probability of any outcome is 1/n, where n is the number of possible outcomes
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Independent
one occuring event DOES NOT change the probability of the other event occuring
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Mutually Exclusive
it is impossible for both events to happen
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Conjunction or Joint probability
Two outcomes are independent. Probability of outcome A and outcome B both happening.
Pr(A & B) is Pr(A) * Pr(B)
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Example of Conjunction or Joint Probability
I flip a coin twice. What is the probability that the coin lands heads first and tails second (HT)?
Pr (H in first flip) = 1/2 and Pr (T in second flip) = 1/2, so Pr(HT)= 1/2 * 1/2 = 1/4
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Disjunction
The probability of either outcome A or outcome B occuring.
Denoted Pr(A \/ B) or Pr (A or B), is Pr(A) + Pr(B) - Pr(A&B).
If the outcomes are independent, Pr (A \/ B) = Pr (A) + Pr(B) - Pr(A) * Pr (B)
If outcomes are mutually exclusive, so Pr(A&B) must equal 0, so Pr(A \/ B) = Pr(A) + Pr(B)
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