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Uniform distribution and moment generating function?
See: http://en.wikipedia.org/wiki/Uniform_distribution_(continuous)
What are the characteristics of continuous distribution?
The probability distribution function (pdf) is defined over a domain which contains at least one interval in which the pdf is positive for all values. Usually the domain is either the whole of the real numbers or the positive real numbers, but it can be a finite interval: for example, the uniform continuous distribution. Also, trivially, the pdf is always non-negative, the integral of the pdf, over the whole real line, equals 1.
In Excel what function will give you an estimate of the value of a continuous random variable if you know the probability of that variable?
There are infinitely many continuous probability functions and there is no information whatsoever in the question to determine the nature of the distribution: uniform, Normal, Student's t, Chi-square, Fisher's F, Gamma, Beta, Lognormal, etc, etc. Second, every continuous function must have at least two points for which the probability is the same. There is no information as to which of these two (or more) points is the relevant one. There can therefore be no answer.
What is the probability of choosing a number greater than 21 if a number is randomly chosen between 1 and 50?
Assuming the uniform continuous distribution, the answer is 29/49. With the uniform discrete distribution, the answer is 29/50.
Is the graph for nonuniform motion a curve line?
No. First of all, it depends on what is being graphed. Also, a distance-time graph of non-uniform motion could be any continuous line other than a straight line - for example a saw-tooth shape.
Why The exponential function x ex is continuous but not uniform continuous?
fist disply your anser
Uniform distribution and moment generating function?
See: http://en.wikipedia.org/wiki/Uniform_distribution_(continuous)
State and prove uniform limit theorem?
There exists an N such that for all n>N, for any x. Now let n>N, and consider the continuous function . Since it is continuous, there exists a such that if , then . Then so the function f(x) is continuous.
What is the difference between continuous and uniformly continuous functions?
The way I understand it, a continuos function is said not to be "uniformly continuous" if for a given small difference in "x", the corresponding difference in the function value can be arbitrarily large. For more information, check the article "Uniform continuity" in the Wikipedia, especially the examples.
Similarity between the uniform and normal probability distributions?
They are continuous, symmetric.
Does this means that all symmetric distribution are normal Explain?
Don't know what "this" is, but all symmetric distributions are not normal. There are many distributions, discrete and continuous that are not normal. The uniform or binomial distributions are examples of discrete symmetric distibutions that are not normal. The uniform and the beta distribution with equal parameters are examples of a continuous distribution that is not normal. The uniform distribution can be discrete or continuous.
What are the characteristics of continuous distribution?
The probability distribution function (pdf) is defined over a domain which contains at least one interval in which the pdf is positive for all values. Usually the domain is either the whole of the real numbers or the positive real numbers, but it can be a finite interval: for example, the uniform continuous distribution. Also, trivially, the pdf is always non-negative, the integral of the pdf, over the whole real line, equals 1.
What is the variance of the uniform distribution function?
the variance of the uniform distribution function is 1/12(square of(b-a)) and the mean is 1/2(a+b).
In Excel what function will give you an estimate of the value of a continuous random variable if you know the probability of that variable?
There are infinitely many continuous probability functions and there is no information whatsoever in the question to determine the nature of the distribution: uniform, Normal, Student's t, Chi-square, Fisher's F, Gamma, Beta, Lognormal, etc, etc. Second, every continuous function must have at least two points for which the probability is the same. There is no information as to which of these two (or more) points is the relevant one. There can therefore be no answer.
What is Continuous Manufacturing?
It is the continuous production of food for emample that is uniform in shape size, and very consistant in products. It operates 24/7, 7 days a week.
What is the important similarity between the uniform and normal probability distribution?
They are both continuous, symmetric distribution functions.
What are some examples of distribution function?
I will assume that you are asking about probability distribution functions. There are two types: discrete and continuous. Some might argue that a third type exists, which is a mix of discrete and continuous distributions. When representing discrete random variables, the probability distribution is probability mass function or "pmf." For continuous distributions, the theoretical distribution is the probability density function or "pdf." Some textbooks will call pmf's as discrete probability distributions. Common pmf's are binomial, multinomial, uniform discrete and Poisson. Common pdf's are the uniform, normal, log-normal, and exponential. Two common pdf's used in sample size, hypothesis testing and confidence intervals are the "t distribution" and the chi-square. Finally, the F distribution is used in more advanced hypothesis testing and regression.
