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The normal distribution is a bell shaped curve. Properly normalized, the area under the curve is 1.0. Start by drawing axes. The Y axis is probability, peaking at 0.4, crossing the X axis at the mean, and the X axis is standard deviation. Draw points (-3, 0.01), (-2, 0.05), (-1, 0.25), (0, 0.4), (+1, 0.25), (+2, 0.05), (+3, 0.01). These are all approximations. Connect the dots, understanding that the curve is asymptotic to the X axis.

For a better picture, as well as an explanation, please see the related link below. This picture also shows you the percentage each area, grouped by standard deviation, or sigma, is. The normal distribution is the second picture on the right. Scroll up to see the picture, call "Normal Distribution".

Q: What is the sketch for a normal distribution?

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No, the normal distribution is strictly unimodal.

Yes. When we refer to the normal distribution, we are referring to a probability distribution. When we specify the equation of a continuous distribution, such as the normal distribution, we refer to the equation as a probability density function.

No. Normal distribution is a continuous probability.

A normal distribution can have any value for its mean and any positive value for its variance. A standard normal distribution has mean 0 and variance 1.

Everything that is normal and can can be distributed easily is known as normal distribution time.

Related questions

The standard normal distribution is a normal distribution with mean 0 and variance 1.

The standard normal distribution is a special case of the normal distribution. The standard normal has mean 0 and variance 1.

le standard normal distribution is a normal distribution who has mean 0 and variance 1

When its probability distribution the standard normal distribution.

No, the normal distribution is strictly unimodal.

The domain of the normal distribution is infinite.

Yes. When we refer to the normal distribution, we are referring to a probability distribution. When we specify the equation of a continuous distribution, such as the normal distribution, we refer to the equation as a probability density function.

The Normal distribution is, by definition, symmetric. There is no other kind of Normal distribution, so the adjective is not used.

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

The normal distribution would be a standard normal distribution if it had a mean of 0 and standard deviation of 1.

A mathematical definition of a standard normal distribution is given in the related link. A standard normal distribution is a normal distribution with a mean of 0 and a variance of 1.

No. Normal distribution is a continuous probability.