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What is the difference between beta and normal distribution?
The probability density functions are different in shape and the domain. The domain of the beta distribution is from 0 to 1, while the normal goes from negative infinite to positive infinity. The shape of the normal is always a symmetrical, bell shape with inflection points on either sides of the mean. The beta distribution can be a variety of shapes, symmetrical half circle, inverted (cup up) half circle, or asymmetrical shapes. Normal distribution has many applications in classical hypothesis testing. Beta has many applications in Bayesian analysis. The uniform distribution is considered a specialized case of the beta distribution. See related links.
In your own words describe the standard normal distribution?
The standard normal distribution is a special case normal distribution, which has a mean of zero and a standard deviation of one.
What is the difference bitween normal distrubution and standard normal distribution?
A normal distribution is defined by two parameters: the mean, m, and the variance s2, (or standard deviation, s).The standard normal distribution is the special case of the normal distribution in which m = 0 and s = 1.
How does the standard normal distribution differ from the t-distribution?
The normal distribution and the t-distribution are both symmetric bell-shaped continuous probability distribution functions. The t-distribution has heavier tails: the probability of observations further from the mean is greater than for the normal distribution. There are other differences in terms of when it is appropriate to use them. Finally, the standard normal distribution is a special case of a normal distribution such that the mean is 0 and the standard deviation is 1.
How critical value is calculated in Kolmogorov-Smirnov test?
if my data followed to a special distribution, how can i calculate the critical value of k-s test in this case?
