1. I was studying histograms and normal distribution. As far as I know, they are two different tools used for calculating probability and statistics. More specifically they help to visualize and it is an effective way to summarize a large amount of data. The main difference is in their math and the way they visualize. A sample of data will form a distribution, and by far the most well-known distribution is the Gaussian distribution, often called the Normal distribution. The distribution provides a parameterized mathematical function that can be used to calculate the probability for any individual observation from the sample space. This distribution describes the grouping or the density of the observations The Normal Distribution is a symmetrical probability distribution where most results are located in the middle and few are spread on both sides. It has the shape of a bell and can entirely be described by its mean and standard deviation. CIToolkit Trainer and Self-Employed Consultant at CIToolkit. The Gaussian distribution is also commonly called the "normal distribution" and is often described as a "bell-shaped curve". If the probability of a single event is p = and there are n = events, then the value of the Gaussian distribution function at value x = is x 10^. For these conditions, the mean number of events is and the standard The probability mass function and the cumulative distribution function formulas of a geometric distribution are given below: PMF: P (X = x) = (1 - p) x - 1 p. CDF: P (X ≤ x) = 1 - (1 - p) x. In addition, the following are the geometric probability formulas for mean, variance, and standard deviation. Mean (or) Expected value = 1/p. A histogram is an effective way to tell if a frequency distribution appears to have a normal distribution. Plot a histogram and look at the shape of the bars. If the bars roughly follow a symmetrical bell or hill shape, like the example below, then the distribution is approximately normally distributed. 1ygsD.

what is normal distribution in math