The normal distribution is an important probability distribution used in statistics. Many real world examples of data are normally distributed. Normal Distribution The normal distribution is described by the mean ( μ) and the standard deviation ( σ ). The normal distribution is often referred to as a 'bell curve' because of it's shape:
The standard normal distribution, also called the z-distribution, is a special normal distribution where the mean is 0 and the standard deviation is 1. Every normal distribution is a version of the standard normal distribution that's been stretched or squeezed and moved horizontally right or left.
The normal distributions are closely associated with many things such as: Marks scored on the test Heights of different persons Size of objects produced by the machine Blood pressure and so on.
Normal distributions come up time and time again in statistics. A normal distribution has some interesting properties: it has a bell shape, the mean and median are equal, and 68% of the data falls within 1 standard deviation. What is a normal distribution?
Properties of the Normal Distribution The Empirical Rule. For all normal distributions, 68.2% of the observations will appear within plus or minus one Skewness. Skewness measures the degree of symmetry of a distribution. The normal distribution is symmetric and has a Kurtosis. Kurtosis
A bell-shaped curve, also known as a normal distribution or Gaussian distribution, is a symmetrical probability distribution in statistics. It represents a graph where the data clusters around the mean, with the highest frequency in the center, and decreases gradually towards the tails. Properties of normal distribution
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what is normal distribution in statistics
