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Sample space
the set of all possible outcomes of an experiment
example: for tossing a coin we can use heads and tails
for rolling a six sided die we can use 1,2, 3, 4, 5, 6
Event
subset of a sample space
example: if a die comes up 2, the event 2,4,6 and 1,2,3 have both occurred
Union
is denoted A u B
it belongs to either a or b or both
Intersection
denoted A n B
is the set of outcome that belong to both A and B
Complement
denoted^{ }A^{c}
is the set of outcomes that do not belong to A
Mutually Exclusive
Probability
is the proportion of times the event would occur in the long run, if the experiment were to be repeated over and over again
denoted: P
The Axioms Of Probability
First Axiom
says that the outcome of an experiment is always in the sample space
Second Axioms
says that the long-run frequency of any event is always between 0 and 100%
Third Axiom
that the probability that the pin is either too short or too long is .02 +.03=.05
that the probability that an event does not occur is equal to 1 minus the probability that it does occur
that it is impossible for an experiment to have no outcome
Data Collection
gather a good representative sample of the population. while in practice the data collection process for these three calculations isn't always the same, for practical reasons, it will be assumed to be
The five steps of Data Collection
1. identity
2. Types of Study
3. Design the Data Collection
4.Gather Data
5. Organize
Steps in Identity
A)Units of population example: tomatoes
B)Variables
C) Type of Variables
I. quantitative
II. categorical
Types of Study
A) observational... we just watch
B) experimental... where we manipulate the variables
What is S.A.S
Simple Random Sample
two ways to ruin randomness
1)the researcher
2) the random person
does the size of the sample have anything to do with the size of the calculation
No, because of the law of large numbers
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