Term
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Definition
A complete set of all possible
distinct outcomes and their probabilities of
occurring
– Sum of these probabilities = 1 |
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Term
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Definition
mean of the probability distribution
(the “expected” value of the random variable x) |
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Term
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Definition
2
= variance of the probability distribution |
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Term
| Binomial Distribution 3 indicators |
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Definition
The binomial distribution has 3 essential properties:
1. Each elementary event is classified into one of
two mutually exclusive and collectively exhaustive
categories, such as success or failure.
2. The probability of success, p, is constant from
trial to trial. Likewise, the probability of failure, 1-
p, is constant from trial to trial.
3. The outcome (success or failure) on a
particular trial is independent of the outcome on
any other trial |
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Term
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Definition
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Term
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Definition
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Term
Shape of the distribution:
p = 0.5 |
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Definition
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Term
| Shape of the distribution:p < 0.5 |
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Definition
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Term
| Shape of the distribution:p > 0.5 |
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Definition
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Term
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Definition
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Term
Hypergeometric
Distribution |
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Definition
x (meaning
that you have x number of successes in your sample), given
knowledge of n, N, and A. |
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Term
Hypergeometric
Distributionn =n |
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Definition
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Term
Hypergeometric
Distribution=N |
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Definition
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Term
Hypergeometric
Distribution=x |
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Definition
| number of successes in sample |
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Term
Hypergeometric
Distribution=A |
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Definition
| number of successes in Population |
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Term
Hypergeometric
Distribution N-A |
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Definition
| number of failures in population |
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Term
| Is hypergeometric with or without replacement? |
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Definition
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Term
Hypergeometric
Distribution μ = |
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Definition
n * A / N (sample size divided by fraction of
successes in the population – makes sense!) |
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Term
Hypergeometric
Distribution σx^2 |
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Definition
= n*A*(N-A) / N2
* {(N-n)/(N-1)} |
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Term
| You can use binomial to approximate the hypergeometric if the sample size is below what percent of the population |
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Definition
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Term
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Definition
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Term
Negative Binomial
Distribution |
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Definition
Determines the probability that the xth success occurs
on the nth trial given a constant probability of success,
p, where n = number of trials until x successes are
observe |
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Term
Negative Binomial
Distribution μ |
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Definition
= x / p (if you are hoping for two successes and p =
0.5, then μ = 2/0.5 = 4; you would expect it to take 4
trials to achieve two successes |
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Term
Negative Binomial
Distribution σn^2 |
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Definition
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Term
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Definition
A special case of the negative binomial distribution
in which we want to find the probability that the
first success occurs on the nth trial (x = 1) |
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Term
| Geometric Distribution μn |
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Definition
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Term
| What is reverse of the binomial distribution |
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Definition
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Term
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Definition
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Term
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Definition
Where P(X=x) represents the probability of
obtaining x successes per area of opportunity
given a knowledge of the parameter λ. |
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Term
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Definition
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Term
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Definition
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Term
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Definition
the “expected” or average number of
successes per area of opportunit |
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