Week 3 Flashcards

1
Q

What is a Random Variable?

A

A function X: Omega -> R that maps an outcome (words) in omega to a number.

Must be defined for all outcomes and single-valued.

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2
Q

When is a random variable discrete/continuous?

A

Discrete when X(omega) (range of X) is countable.

Continuous when X(omega) is uncountable.

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3
Q

How do you measure the probability of a random variable?

A

Map back to the sample space.

Find outcome such that X(outcome) = number.

(X^-1(a) is an event in the event space.)

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4
Q

What is the Probability Mass Function?

A

Px(a) is the probability for the random variable X to take the value a.

The sum of all PMFs for all X(a) should be 1.

Can only describe distribution of discrete random variables.

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5
Q

What is the Cumulative Distribution Function?

A

FX(x) is the probability for the variable X to be at most x.

Works for discrete, continuous and mixed random variables.

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6
Q

What are the properties of a CMF?

A

Non-decreasing.

FX(-infinity) = 0 and FX(infinity) = 1.

P(a < X <= b) = FX(b) - FX(a).

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7
Q

What are the Special Distributions?

A
Bernoulli Distribution: X ~ Bernoulli(p)
Binomial Distribution
Geometric Distribution: PX(k) = (1-p)^k-1 p
(1-p)^k-1 = the first k-1 fails
p = last success
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8
Q

Explain the Binomial Distribution?

A

Pk(x) = (n k) p^k(1-p)^n-k
(n k) = number of combinations
p^k = prob of getting k ps
(1-p)^n-k = prob of getting n-k 1-ps

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9
Q

What is a continuous random variable?

A

A random variable with an uncountable range X(omega).

Continuous CDF.

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10
Q

What changes when working with continuous random variables?

A

The probability of any particular number output is 0.

Can only think about intervals.

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11
Q

How do you measure probability of continuous random variables?

A

Measure the size of a set.

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12
Q

What is the “equiprobable” assumption?

A

X is equally likely to take any value.

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13
Q

What is the Probability Density Function for continuous random variables?

A

A function fx: R -> R+, when integrated over interval [a, b], yields probability of obtaining a <= X <= B.

fx(x) is the probability per unit length.

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14
Q

What is a Continuous Uniform Random Variable?

A

When PDF fx(x) = 1/b-a if a <= x <= b.

CDF = x-a/b-a if a <= x <=b.

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15
Q

What is an Exponential Random Variable?

A

If a random variable has a memoryless property:

P(X > x+a | X > a) = P (X > x)

fx(x) = \e^-\x, if x >= 0

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16
Q

What is the Central Limit Theorem?

A

When many independent random variables are summed, the resulting random variable is a Gaussian.