The Poisson Distribution

The Poisson distribution is applied to:

• model the number of times an event occurs in a fixed interval of time or space

• calculate the probability of success in a series of independent trials

• determine the spread of a dataset

• analyze the relationship between two variables

Deviation from Poisson distribution may indicate some degree of what in the events under study?

• Randomness

• Clustering

• Uniformity

• Independence

Which of the following is an example of an experiment where Poisson distribution can be applied?

• The number of calls received by a switchboard during a given period of time

• The number of apples in a basket

• The height of students in a class

• The weight of a car

Which of the following is NOT an example of an experiment where Poisson distribution can be applied?

• The number of bacteria per small volume of fluid

• The number of customer arrivals at a checkout during a given minute

• The number of machine breakdowns during a given day

• The color of a car

List two examples of experiments where Poisson distribution is applicable.

• Number of emails received per hour and number of decay events per unit time in a radioactive sample

• Height and weight of individuals

• Temperature variations over a day and stock market fluctuations

• Number of students in a class and number of cars in a parking lot

What does X represent in the Poisson Distribution?

• A) The number of events in a period of time or space

• B) The probability of success

• C) The mean of the distribution

• D) The standard deviation

Fill in the blank: The probability distribution of X is called a ______ distribution, and the distribution is written as X~P₀(μ).

• Poisson

• Normal

• Binomial

• Exponential

The experiment in a Poisson distribution consists of:

• a series of independent trials with a constant probability of success

• a fixed number of trials with varying probabilities

• counting the number of events in a fixed interval of time or space

• measuring continuous data over time

In a Poisson distribution, the probability of an event occurring in a given unit of time, area, or volume is described as:

• a constant rate

• a variable rate

• an increasing rate

• a decreasing rate

The relationship between the number of events in a Poisson distribution is:

• directly proportional to the square of the mean

• inversely proportional to the mean

• directly proportional to the mean

• independent of the mean