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Flashcards in Problem 1 Deck (18)
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1
Q

Elementary outcome

A

One possible outcome of the probability experiment

ex.: heart 6 ( in a deck )

2
Q

Sample space

A

Set of all possible elementary outcomes

ex. : when tossing a coin only 2 outcomes are possible in the SS
ex. : all cards in a deck

3
Q

Event

A

An outcome or set of outcomes of a random phenomenon

  • -> every event is an elementary outcome but not other way round
    ex. : heart card ( in a deck), so subset of the SS
4
Q

Disjoint

A

Dependent

–> one event influences the other

“when A happens, B can’t” , thus the 2 events have no outcome in common and so can never occur together

ADDITION RULE (or)

5
Q

Not Disjoint/Joint

A

Independent

–> one event doesn’t influence the outcome of the other

MULTIPLICATION RULE (and)

6
Q

Probability range

A

Number between 0 and 1

0≤ P(A) ≤1

7
Q

Complement rule

A

Finding out what the probability is that an event doesn’t occur

P(A) = 1-P(𝐴𝐶)

ex. : Probability that treatment is effective is 30%
- -> 1-0.3=0.7

8
Q

Random phenomenon

A

Refers to outcomes that we cannot predict but that nonetheless have a regular distribution in very many distributions

9
Q

Probability

A

Refers to the proportion of times the event occurs in many repeated trials of a random phenomenon

10
Q

Trials are independent if …

A

the outcome of one trial doesn’t influence the outcome of any other trial

P(A and B) = P(A) x P(B)

MULTIPLICATION RULE

11
Q

Random variable

A

Refers to a variable whose value is a numerical outcome of a random process

–> its distribution can be discrete vs continuous

12
Q

Probability distribution

A

Indicates what the possible values of X are + how probabilities are assigned to those values

–> can be described by a density curve

13
Q

Continuous random variable

A

Refers to a variable whose value is obtained by measuring

–> probability that X is between an interval of numbers is the area under the density curve

ex.: height of students in class, weight of students in class

14
Q

Discrete random variable

A

Refers to a variable whose value is obtained by counting

ex.: number of students present, number of red marbles in a jar

–> X has a countable number of possible values (Probability histogram)

15
Q

Density curve

A

Describes the probability distribution of a continuous random variable

–> probability of any event is the area above or below the curve

16
Q

Normal distribution

A

Is a type of continuous probability distribution

17
Q

Expected value

A

Refers to a predicted value of a variable, calculated as the sum of all possible values each multiplied by the probability of its occurrence

18
Q

Conditional probability

A

P(B given A) = P(A and B) x P (A)