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You could draw a Probability Plot: "The probability plot ... is a graphical technique for assessing whether or not a data set follows a given distribution such as the normal or Weibull. "The data are plotted against a theoretical distribution in such a way that the points should form approximately a straight line. Departures from this straight line indicate departures from the specified distribution." Source: Online Engineering Statistics Handbook http://www.itl.nist.gov/div898/handbook/eda/section3/probplot.htm

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Q: How can you prove that a random variable follows the Poisson distribution?
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What is the Test for normal distribution?

Normal Distribution is a key to Statistics. It is a limiting case of Binomial and Poisson distribution also. Central limit theorem converts random variable to normal random variable. Also central limit theorem tells us whether data items from a sample space lies in an interval at 1%, 5%, 10% siginificane level.


How do you get the median of a continuous random variable?

You integrate the probability distribution function to get the cumulative distribution function (cdf). Then find the value of the random variable for which cdf = 0.5.


What is meant by probability distribution?

I will give first the non-mathematical definition as given by Triola in Elementary Statistics: A random variable is a variable typicaly represented by x that has a a single numerical value, determined by chance for each outcome of a procedure. A probability distribution is a graph, table or formula that gives the probabability for each value of the random variable. A mathematical definition given by DeGroot in "Probability and Statistics" A real valued function that is defined in space S is called a random variable. For each random variable X and each set A of real numbers, we could calculate the probabilities. The collection of all of these probabilities is the distribution of X. Triola gets accross the idea of a collection as a table, graph or formula. Further to the definition is the types of distributions- discrete or continuous. Some well know distribution are the normal distribution, exponential, binomial, uniform, triangular and Poisson.


What will be the sampling distribution of the mean for a sample size of one?

It will be the same as the distribution of the random variable itself.


What are the 2 conditions that determine a probability distribution?

The value of the distribution for any value of the random variable must be in the range [0, 1]. The sum (or integral) of the probability distribution function over all possible values of the random variable must be 1.