Chapter 6 - Random Variables Flashcards

0
Q

probability distribution

A

gives it’s possible values and their probabilities

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1
Q

random variable

A

takes numerical values that describe the outcomes of a chance process

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2
Q

discrete random variables

A

random variable that can take one of a finite number of distinct outcomes
“the number of…”

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3
Q

mean (expected value) of discrete random variable

A

multiply each value by It’s probability then add all products

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4
Q

continuous random variable

A

random variable that can take any numerical value within a range of values, the range may be infinite or bounded
“the amount of…”
measures something

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5
Q

if y = a + bx is a linear transformation of the random variable x, then

A

-probability distribution of Y has the same shape as probability of x if b>0

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6
Q

independent random variables

A

if x tells us nothing about y and vice verses

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7
Q

center of linear transformation

A

mew y = bmewx

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8
Q

spread of linear transformation

A

oy= |b|ox

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9
Q

when we perform several independent trials of the same chance process & record the # of times a certain outcome occurs

A

binomial setting

BINS

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10
Q

count of X successes in binomial setting

A

binomial random variable

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11
Q

probability of distribution X with parameters n and p
n = number of trials
p = probability

A

binomial distribution

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12
Q

use binompdf when

A

x = k

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13
Q

use binomcdf when

A

x less than or equal to k

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14
Q

mean of binomial random variable

A

mewx = np

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15
Q

ox of binomial random variable

A

square root of np(1-p)

16
Q

geometric setting

A

perform independent trials of the same chance process and record # of trials it takes to get one success

17
Q

number of trials Y that it takes to get a success in a geometric setting

A

geometric random variable

18
Q

probability of Y with parameter p, probability of success on any trial

A

geometric distribution

19
Q

use geometpdf when

A

P(y=k)

20
Q

use geometcdf when

A

P(Y less than or equal to k)