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Q
uantitative
R
easoning &
P
roblem
S
olving
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© 2014 Pacific Crest
W
hat Do You Already Know?
Tapping into your existing knowledge
1. What is the largest value the probability of an event can assume?
2. What is the smallest value the probability of an event can assume?
3. What is always true for the sum of probabilities for all events in a sample space?
4. What are some probability distributions that you know of?
5. Of these distributions, what characteristics can you share about them?
M
athematical Language
Terms and notation
binomial distribution
— a discrete distribution that arises when counting the number of occurrences
of successes in a series of trials where each trial has the same probability of success
continuous random variable
— a random variable that can take on an uncountable number of
values
cumulative probability distribution
— the distribution found by totaling all likelihoods less than
or equal to
x
, for each
x
in the sample space
discrete random variable
— a random variable restricted to a countable number of possible values.
normal distribution
— a continuous probability distribution that describes the likelihood that an
observation will fall between any two numbers in a symmetrical fashion and most of the results are
situated around the probability’s distribution mean
poisson distribution
— a discrete distribution that describes the likelihood of a certain number of
independent events occurring in a fixed time
random variable
— a quantity whose value follows a pattern of randomness
skewed
— A distribution that is not symmetric is skewed. The direction of the skew is given by the
location of the “tail” of the distribution.
symmetric
— a distribution is symmetric when a vertical line can be drawn down the middle and the
probability of being any given distance on one side is the same as being that distance on the other
side
uniform distribution
— a distribution that describes a sample space where all events are equally likely