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Biostatistics: Lecture 5 (Sample Space and Events)
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these are also called random experiments
statistical experiments
what are the characteristics of statistical experiments
1. A listing of all outcomes is possible or at least conceivable.
2. Any outcome cannot be predicted with certainty.
sample space is denoted by what?
S
this is a set of all possible outcomes of a statistical experiment
sample space
this is a subset of a sample space and is denoted by any capital letter of the english alphabet except for S
event
an event can either be
or
simple or compound
this is a set containing of only one element of the sample space
simple event
this can be expressed as the union of the simple events
compound event
this is a set that contains no element
null or empty space
what do you call two events that cannot occur simultaneously
mutually exclusive events
two events are
when there is no reason to expect one event rather than the other to occur
:having the same probability of occurence
equally likely events
identify if mutually exclusive events or equally likely events:
the event of choosing a male respondent and the event of choosing a pregnant respondent
mutually exclusive events
identify if mutually exclusive events or equally likely events:
tossing a fair coin
equally likely events
identify if mutually exclusive events or equally likely events:
tossing a fair, six-sided die
equally likely events
identify if mutually exclusive events or non mutually exclusive events:
events of choosing a bag and color yellow
not mutually exclusive events
identify if mutually exclusive events or non mutually exclusive events:
events of losing a game and scoring
non mutually exclusive events
identify if mutually exclusive events or non mutually exclusive events:
the probability of choosing an ace or a queen from a standard deck of cards
mutually exclusive events
can an event be mutually exclusive and equally likely
Equally likely events may be mutually exclusive or not mutually exclusive. ⇔ Mutually Exclusive events may be equally likely or not equally likely.
this is a function whose value is a real number determined by each element ins a sample space
random variable
random variables can be
or
discrete or continuous
this type of random variable have a countable number of outcomes
discrete random variable
this type of random variable have an infinite continuum of possible values
continuous random variable
this maps the possible values of x against their perspective probabilities of occurrence, P(x)
probability function
P(x) is a number from
to
0 to 1.0
the area under a probability function is always
1
this is the most important continuous probability distribution in the field of statistics
normal distribution
what do you call the bell-shaped curve graph of the normal distribution
normal curve
the normal distribution is also called
Gaussian distribution
the normal distribution is named after the mathematician
Carl Friedrich Gauss (1777-1855)
what are the properties of the normal distribution
1. It is symmetric with respect to a vertical axis passing through the mean µ.
2. The mean, median, and mode are equal.
3. The tails are asymptotic relative to the horizontal line.
4. The total area under the normal curve and above the horizontal axis is 1 or 100%.
Author
aisbear
ID
364693
Card Set
Biostatistics: Lecture 5 (Sample Space and Events)
Description
Updated
2024-03-30T01:55:29Z
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