Business Stats ch 5-7
Special Rule of Addition
(A or B)= P(A)+P(B)
All of the above
A normal distribution can be described as a/an ____ distribution.
minimum and maximum times to load a delivery truck.
A random variable, time to load a delivery truck, is uniformly distributed. The distribution is defined by the
rectangular.
A uniform distribution's shape is:
a collection of outcomes from an experiment.
An event is:
symmetrical.
For a binomial distribution with n = 15, as π changes from 0.05 toward 0.50, the distribution will become:
each trial is limited to two outcomes.
For a binomial probability distribution:
equal to the mean of the distribution.
For any probability distribution, the expected value is:
the distribution is defined by the mean and standard deviation of the random variable
If a random variable is normally distributed:
may be any value within a certain range.
In a continuous probability distribution, the random variable:
all possible outcomes of an experiment.
In an experiment, a random variable represents:
the probabilities for all possible outcomes must sum to 1.00.
In general, a discrete probability distribution requires that:
General Rule of Addition
P(A or B)= P(A)+P(B)-P(A+B)
Special Rule of Multiplication
P(A&B)=P(A)P(B/A)
Complement Rule
P(x)= 1-P(*x)
the likelihood that an event will happen.
Probability is defined as:
the probability of two events, which are not mutually exclusive.
The General Rule of Addition is used to compute:
the probability of two or more dependent events.
The General Rule of Multiplication is used to compute:
the probability of two or more mutually exclusive events.
The Special Rule of Addition is used to compute:
in a permutation order is important and in a combination order is not important.
The difference between a permutation and a combination is:
zero.
The joint probability of two mutually exclusive events is:
the Poisson probability distribution.
The mean and variance are equal for:
continuous
The normal distribution is a _____ distribution.
one event affects the likelihood of another event.
Two events are not independent if:
the complement rule.
When we subtract the probability of an event from 1, we are using the:
Probability values range from 0 to 1, inclusive.
Which of the following is a correct statement about probability?
The outcome of any trial is dependent on the outcomes of previous trials.
Which of the following is not a characteristic of a binomial distribution?
Independent
Which of the following is not a type of probability?
All of the above are correct.
Which of the following statements is correct regarding the standard normal distribution?
A probability distribution summarizes all possible experimental outcomes and their probability.
Which of the following statements is true about a probability distribution?
The Poisson probability distribution
Which probability distribution is applied when the probability of a success is very small?
probability distribution
a listing of all the outcomes of an experiment and the probability associated with each other
experiment
a process that leads to the occurrence of one and only on of several possible results
objective
based on facts
general
both aren't mutually exclusive, conditional
2.71828
e
classical probability
favorable outcomes/total possible outcomes
subjective
has opinion onit
special
mutually exclusive
Combination formula
nCr a group,committee
Permutation formula
nPr how many different arrangments
empirical propability
number of times the event occurs/total number of observations
law of large numbers
over a large number of trials, the empirical probability of an event will approach its true probability
subjective concept of probability
the likelihood (probability) of a particular event happening that is assigned by an individual based on whatever information is available
mulitplication formula
total outcomes=(m)(n)
