Which of the following is true about the hypergeometric distribution quizlet?

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1. Math
2. Probability

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Definitions and Info

Terms in this set (32)

Probability

A measure of the likelihood that an event in the future will happen. It can only assume a value between 0 and 1. A value near zero means the event is not likely to happen. A value near one means it is likely.

3 ways of assigning probability

-Classical
-Empirical
-Subjective

Experiment

The observation of some activity or the act of taking some measurement. An experiment can have 2 or more results.

Outcome

the particular result of an experiment

Event

the collection of one or more outcomes of an experiment

Characteristics of a Binomial Probability Distribution

-There are only two (bi) possible outcomes on a particular trial of an experiment (i.e. late or early).
-The outcomes are mutually exclusive.
-The random variable is the result of counts.
-Each trial is independent of any other trial.

The General Rule of Addition

If A and B are two events that are not mutually exclusive, then (A or B) is given by the following formula...
P(A or B)= P(A)+P(B)-P(A and B) --- this formula will be on the formula page we are given for the test.

Characteristics of Hypergeometric Distribution

-There are only 2 possible outcomes.
-The probability of a success is not the same on each trial.
-It results from a count of the numbers of successes in a fixed number of trials.

Finite Population

A population consisting of a fixed number of known individuals, objects, or measurements.
I.e. - the number of students in a class; -the number of cars in the parking lot; - the number of homes built in Blackmoor.

Characteristics of a Normal Probability Distribution

-It is a listing of all possible outcomes and their corresponding probability of occurrence.
-It is bell-shaped and has a single peak at the center of the distribution.
-The arithmetic mean, median, and mode are equal.
-The total area under the curve is 1.00; half the area under the normal curve is to the right of this center point and the other half to the left of it. It is symmetrical about the mean.
-It is asymptotic: the curve gets closer and closer to the X-axis but never actually touches it. To put it another way, the tails of the curve extend indefinitely in both directions.
-The location of a normal distribution is determined by the mean, the dispersion or spread of the distribution is determined by the standard deviation.

Random Variable

a quantity resulting from an experiment that, by chance, can assume different values.

Discrete Random Variable

can assume only certain clearly separated values. It is usually the result of counting something.

Continuous Random Variable

can assume an infinite number of values within a given range. it is usually the result of some type of measurement.

Characteristics of a Discrete Distribution

-The sum of the probabilities of the various outcomes are 1.00.
-The probability of a particular outcome is between 0 and 1.00.
-The outcomes are mutually exclusive, (The occurrence of one event means that none of the other events can happen at the same time.)

Which of the following is a correct statement about a probability?
a. It may range from 0 to 1.
b. It may assume negative values.
c. It may be greater than 1.
d. It cannot be reported to more than 1 decimal place.
e. All the above are correct.

a. It may range from 0 to 1.

An experiment is a ...?
a. collection of events
b. collection of outcomes
c. always greater than 1
d. the act of taking a measurement or the observation of some activity
e. none of the above is correct

d. the act of taking a measurement or the observation of some activity

Which of the following is not a type of probability?
a. subjective
b. independent
c. relative frequency
d. relative frequency
d. classical

d. independent

when we find the probability of an event happening by subtracting the probability of the event not happening from 1, we are using...
a. subjective probability
b. the complement rule
c. the general rule of addition
d. the special rule of multiplication
e. joint probability

b. the complement rule

When we determine the number of combinations
a. we are really computing a probability
b. the order of the outcomes is not important
c. the order of the outcomes is important
d. we multiple the likelihood of two independent trials
e. none of the above

b. the order of the outcomes is not important

The difference between a permutation and a combination is..
a. in a permutation order is important and in a combination it is not.
b. in a permutation order is not important and in a combination is it important.
c. a combination is based on the classical definition of probability
d. a permutation is based on the classical definition of probability
e. none of the above

a. in a permutation order is important and in a combination is it not

The difference difference between a random variable and a probability distribution is...
a. a random variable does not include the probability of an event
b. a random variable can only assume whole numbers
c. a probability distribution can only assume whole numbers
d. none of the above

a. a random variable does not include the probability of an event

Which of the following is not a requirement of a binomial distribution?
a. a constant probability of success
b. only two possible outcomes
c. a fixed number of trails
d. equally likely outcomes

d. equally likely outcomes

Which of the following is not a requirement of a probability distribution?
a. Equally likely probability of a success
b. sum of the possible outcomes is 1.00.
c. the outcomes are mutually exclusive.
d. the probability of each outcome is between 0 and 1

a. equally likely probability of a success.

For a binomial distribution...
a. n must assume a number between 1 and 20 and 25.
b. probability must be a multiple of .10.
c. there must be at least 3 possible outcomes.
d. none of the above

d. none of the above

Which of the following is a major difference between the binomial and the hypergeometric distribution?
a. the sum of the outcomes can be greater than 1 for the hypergeometric
b. the probability of a success changes from trial to trial in the hypergeometric distribution
c. the number of trials changes in the hypergeometric distribution
d. the outcomes cannot be whole numbers in the hypergeometric distributions

b. the probability of a success changes from trial to trial in the hypergeometric distribution

In a continuous probability distribution ...
a. only certain outcomes are possible
b. all the values within a certain range are possible
c. the sum of the outcomes is greater than 1.00
d. none of the above

b. all the values within a certain range are possible

The expected value of a probability distribution..
a. is the same as the random variable
b. is another term for the mean
c. is also called the variance
d. cannot be greater than 1

b. is another term for the mean

The normal distribution is a ...
a. discrete distribution
b. continuous distribution
c. positively skewed distribution
d. none of the above

b. continuous distribution

Which of the following are characteristics of the normal distribution?
a. it is a symmetric distribution
b. is is bell-shaped
c. is it asymptotic
d. all of the above

d. none of the above

Which of the following are correct statements about a normal distribution?
a. it cannot assume negative numbers
b. it is defined by its mean and standard deviation
c. all normal distributions have a variance of at least 1.
d. all of the above are correct

b. it is defined by its mean and standard deviation

Which of the following statements is correct regarding the standard normal distribution?
a. it is also called the z distribution
b. any normal distribution can be converted to the standard normal distribution
c. the mean is 0 and the standard deviation is 1
d. all of the above are correct

d. all of the above are correct

...

...

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Which of the following is true about hypergeometric distribution?

Which of the following is a requirement for use of hypergeometric distribution?

Which of the following is true regarding the normal distribution?

Which of the following is a major difference between the binomial and the hypergeometric distribution?