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Data_Distribution_Analysis

normal distribution is a symmetric distribution where most of the observations cluster around the central peak and the probabilities for values further away from the mean taper off equally in both directions. Extreme values in both tails of the distribution are similarly unlikely.

As with any probability distribution, the parameters for the normal distribution define its shape and probabilities entirely. The normal distribution has two parameters, the mean and standard deviation.

The normal distribution does not have just one form.Most values cluster around the mean. On a graph, changing the mean shifts the entire curve left or right on the X-axis.s based on the parameter values, as shown in the graph above.

The standard deviation represents the typical distance between the observations and the average.On a graph, changing the standard deviation either tightens or spreads out the width of the distribution along the X-axis. Larger standard deviations produce distributions that are more spread out.This property is part of the Empirical Rule, which describes the percentage of the data that fall within specific numbers of standard deviations from the mean for bell-shaped curves.

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