Would Network Traffic Rate Estimates Follow a Pareto or Normal Distribution?

In summary, the conversation discusses the distribution of estimated rates when traffic in a network is generated from a Pareto distribution. The individual values drawn from the distribution will each be Pareto distributed, but the sample average will be approximately normal due to the central limit theorem. The distinction between the individual values and sample average is clarified.
  • #1
mloo01
9
0
I have a question that is confusing me.

If traffic in a network is being generated from a Pareto distribution,
And I am estimating this traffic rate at each packet arrival,
If I was to take the previous x estimated rates as a sample of data,
Would the distribution of these estimated rates still be Pareto or would they be more of a Normal distribution?

Any comments would be great!
 
Physics news on Phys.org
  • #2
if you take random samples from a pareto distribution, the individual values you draw will each be pareto distributed. However the central limit theorum says that the sample average will be approximately normal (if suitable conditions are met).ie, suppose you draw random values [tex]x_1, x_2, x_3, x_4...x_n[/tex].

Each value [tex]x_i[/tex] is pareto distributed. However the sample average [tex]\bar{x} = \frac{\sum x_i}{n}[/tex] is approximately normalDoes that make the distinction clearer?
 
  • #3
Yes that's great thank you
 

FAQ: Would Network Traffic Rate Estimates Follow a Pareto or Normal Distribution?

What is sample data from distributions?

Sample data from distributions refers to a subset of data that has been collected or observed from a larger population. This data is used to make inferences and draw conclusions about the larger population.

Why is it important to collect sample data from distributions?

Collecting sample data from distributions allows us to make generalizations about the larger population. It also helps us to understand the characteristics and patterns of the population.

How is sample data from distributions collected?

Sample data from distributions can be collected through random sampling, where participants are selected at random from the population. Other methods include stratified sampling, cluster sampling, and convenience sampling.

What are some common types of distributions?

Some common types of distributions include the normal distribution, the uniform distribution, the binomial distribution, and the exponential distribution.

How is sample data from distributions analyzed?

Sample data from distributions can be analyzed using descriptive statistics, such as measures of central tendency and variability. It can also be analyzed using inferential statistics, such as hypothesis testing and confidence intervals, to make inferences about the larger population.

Back
Top