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the normal distribution is a bell shape and expeonential is rectangular

Q: How does the shape of the normal distribution differ from the shapes of the uniform and exponential distributions?

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A discrete probability distribution is defined over a set value (such as a value of 1 or 2 or 3, etc). A continuous probability distribution is defined over an infinite number of points (such as all values between 1 and 3, inclusive).

No, a distribution can have infinitely many moments: the first is the mean, the second variance. Then there are skewness (3), kurtosis (4), hyperskewness (5), hyperflatness (6) and so on.If mk represents the kth moment, thenmk = E[(X - m1)k] where E is the expected value.It is, therefore, perfectly possible for m1 and m2 to be the same but for the distribution to differ at the higher moments.

it differs becaus eit shows differ amount of data and it gives a differ piont of point of numbers

part 2 means to be 20 cents. If the standard deviation of the distribution of the difference between sample means is 28 cents and we are testing the null hypothesis at the 95% confidence level, which statement is true?

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Cubic Growth is x^a, a being some constant, while exponential growth is a^x. Exponential growth ends up growing MUCH faster than cubic growth.

The standard normal distribution has a mean of 0 and a standard deviation of 1.

There are so many different ways they can differ I can't really cover them all. Virtually anything in Linux distributions can be replaced. Even the kernel can be swapped out with alternate builds. Usually, the most common changes are the default desktop and desktop applications for desktop distributions.

Its non uniform.

An exponential function of the form a^x eventually becomes greater than the similar power function x^a where a is some constant greater than 1.

Linux differs from traditional operating system primarily in the fact that most distributions are available free of cost.

Yes.

Every function differs from every other function. Otherwise they would not be different functions!

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Louisiana has not adopted the Uniform Commercial Code in its entirety. Instead, Louisiana has its own version of commercial laws that differ from the UCC.

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.