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A statistical distribution, or probability distribution, describes how values are distributed for a field. In other words, the statistical distribution shows which values are common and uncommon. There are many kinds of statistical distributions, including the bell-shaped normal distribution.

The distribution is a mathematical function that describes the relationship of observations of different heights. A distribution is simply a collection of data, or scores, on a variable. Usually, these scores are arranged in order from smallest to largest and then they can be presented graphically.

The distribution of a data set is the shape of the graph when all possible values are plotted on a frequency graph (showing how often they occur). Usually, we are not able to collect all the data for our variable of interest. Therefore we take a sample. This sample is used to make conclusions about the whole data set.

A histogram is the most commonly used plot type for visualizing distribution. It shows the frequency of values in data by grouping it into equal-sized intervals or classes (so-called bins). In such a way, it gives you an idea about the approximate probability distribution of your quantitative data.

Consider rolling a six-sided die. You have an equal probability of obtaining all six numbers on your next roll, i.e., obtaining precisely one of 1, 2, 3, 4, 5, or 6, equaling a probability of 1/6, hence an example of a discrete uniform distribution.

Steps to Making Your Frequency Distribution Step 1: Calculate the range of the data set. ... Step 2: Divide the range by the number of groups you want and then round up. ... Step 3: Use the class width to create your groups. ... Step 4: Find the frequency for each group.

Normal distribution, chi-square distribution, binomial distribution, poisson distribution, and uniform distribution are some of the many different classifications of probability distributions.