STAT 2040 Final: Second Half Summary Notes
24 Mar 2016
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Can take on an in nite number of possible values in an interval. Common examples include weights, heights, and time to an event. The simplest continuous distribution is the uniform distribution (all intervals of equal length are equally likely to occur) f(x) x example: Suppose a random variable x has the continuous uniform distribution with a minimum of. Many variables have distributions that are approximately normal and therefore display a normal distribution. Normal distributions have two parameters and . is both the mean and the median. The standard normal distribution is a normal distribution with =1 and =0. We can convert x into a variable having the standard normal distribution if we let: If x is the mean of n independent observations from a normal distribution with mean and a standard deviation , then: For large sample sizes the sampling distribution of the sample mean will be approximately normal regardless of the distribution from which we are sampling.
