Ch. 5 Stats Vocab

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22 Terms

1
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random process

generates outcomes that are determined by chance

  • unpredictable in the short run

  • eventually has a regular and predictable pattern in the long run

2
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probability

a number between 0 and 1 that describes the proportion of times the outcome would occur in a very long series of repetitons

  • express as decimal, fraction, or percentage.

3
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empirical probability

likelihood of an event occurring based on actual experiments or observations

  • use approximates for real trial

4
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theoretial probability

calculated likelihood of an event occurring, based on the mathematical model rather than experimental data

  • P(E) = (# of ways an event can occur)/(total possible outcome)

5
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law of large numbers

as the number of trials increases, the relative frequency approaches theoretical probability

6
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basic rules of probability

  1. if all outcomes in sample space are equally likely, the probability that event A occurs is P(A) = (# of outcomes in event A)/(total # outcomes in sample space

  2. probability of any even is a number between 0 and 1

  3. all possible outcomes together must have probabilities that add up to 1

  4. the probability that an event does not occur is 1 minus probabillity of the event occuring

7
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complement rule

probability that an event will NOT occur

  • 1 minus the probability of the event is the complement

  • P(Ac) = 1 - P(A)

8
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law of averages

a common misconception of past outcomes of a random event being able to influence future results

  • “balancing out”

  • misguided belief

9
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sample space

list of all possible outcomes

10
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simulation

imitation of chance behavior, based on a model that accurately reflects the situation

  • assign numbers

  • determine what you are counting and record

11
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probability model

description of some chance process that MUST consist of two parts

  1. sample space

  2. probability for each outcome

12
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event

any collection of outcomes from some chance process

13
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mutually exclusive (disjoint)

two events that have no common outcomes, can never occur together

  • P(A and B) = 0

  • NEVER independent

14
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visual images for summarizing sample space

can make either two-way table or venn diagram

  • make sure to properly isolate each response in the proper section

15
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P(A U B)

union; probability that either event A, event B, or both events occur

  • P(A) + P(B) - P(A ∩ B)

16
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conditional probability

probability that one event occurs given that another event is known to happen

  • P(A|B)

17
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calculating conditional probability

P(A|B) = P(A ∩ B) ÷ P(B)

18
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independent events

if knowing whether or not one event has occurred does not impact the probability that the other event will happen

  • yes: P(A) = P(A|B)

  • no: P(A) ≠ P(A|B)

  • must be exact same value

19
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multiplication rule

P(A ∩ B) = P(A) × P(B)

  • specifically only for independent events

20
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tree diagram

shows the sample space of a chance process involving multiple stages

  • Every probability after the first stage is conditional

21
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general formula for showing independence

P(A) ≠ P(A|B)

Therefore, the events “A” and “B” are not independent. Knowing that “B” happened increases/decreases the probability of “A.”

  • increases —> value is greater than 50%

  • decreases —> value is less than 50%

22
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general formula for discussing simulation results

On average, according to my simulation, ____.

  • must include units if available

  • include the real mean, even if in parentheses