Statistics question (poisson distribution, multivariate )

In summary, the conversation discusses finding the probability of receiving more than 2 calls per minute at a corporation's switchboard, as well as determining marginal densities, means, and variances of joint probability distributions. The individual seeking assistance expresses uncertainty and lack of understanding in solving the problems.
  • #1
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Homework Statement



On average, 2.5 telephone calls per minute are received at a corporation's switchboard. Making appropriate assumptions about the distribution ( provide justification ), find the probability that at any given minute there will be more than 2 calls.

Homework Equations



No idea.

The Attempt at a Solution



No idea.

Homework Statement


Let the joint p.d.f of X and Y, f(x,y), be given by

.....x
...1...2...3
y..1...0.3..0.2..0.1
...2 ...0.1..0.1..0.2
(ignore the dots)
a) Determine marginal densities
b) compute the means and variances of X and Y
c) Calculate sigma(?) xy = cov (X,Y) and the correlation coefficient ρ. Are X and Y independent ?
d) Let Z = X+Y. determine k(z)+P(Z=z), z = 2,3,4,5. determine the mean and variance.

Homework Equations



good question

The Attempt at a Solution



I don't have one

Well, how do I do this? I do not understand it. If anybody has some insight on either problem, I'd appreciate it.
 
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  • #2
Got the first one now. About the 2nd one - I THINK I now have b and partly c. but c required the marginal densities, correct ( for the correlation coefficient ) ? I don't know how to do that. The example in the book just tells me ok here it is..without explaining how to get it.
 

Related to Statistics question (poisson distribution, multivariate )

1. What is the Poisson distribution and how is it used in statistics?

The Poisson distribution is a probability distribution that is used to model the number of events that occur in a specific time interval or space. It is often used in situations where the number of events is rare and the events occur independently of each other. It is also used to estimate the probability of a certain number of events occurring in a given time period.

2. How do you calculate the probability using the Poisson distribution?

The probability of a certain number of events occurring in a specific time interval can be calculated using the Poisson distribution formula: P(x;λ)= (e^(-λ)*λ^x) / x! , where λ is the mean number of events, and x is the number of events.

3. What is the difference between the Poisson distribution and the normal distribution?

The Poisson distribution is used to model the number of rare events occurring in a specific time interval, while the normal distribution is used to model continuous data that follows a bell-shaped curve. The Poisson distribution is discrete, while the normal distribution is continuous. Additionally, the mean and variance of the Poisson distribution are equal, while in a normal distribution, the variance is equal to the square of the standard deviation.

4. How is the Poisson distribution related to the concept of independence in statistics?

The Poisson distribution assumes that the events occur independently of each other. This means that the occurrence of one event does not affect the probability of another event occurring. This assumption is important in using the Poisson distribution for modeling rare events.

5. What is multivariate analysis and how is it used in statistics?

Multivariate analysis is a statistical technique used to analyze and understand the relationships between multiple variables in a dataset. It involves the use of various statistical methods, such as regression analysis, factor analysis, and principal component analysis, to identify patterns and relationships between variables. It is commonly used in fields such as social sciences, marketing, and business analytics.

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