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Q: Are all unimodal distributions normal

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It is not necessary that all symetric distribution may be normal.

I think yes or no

No. The Normal distribution is symmetric: skewness = 0.

If the two distributions can be assumed to follow Gaussian (Normal) distributions then Fisher's F-test is the most powerful test. If the data are at least ordinal, then you can use the Kolmogorov-Smirnov two-sample test.

The Normal distribution is a probability distribution of the exponential family. It is a symmetric distribution which is defined by just two parameters: its mean and variance (or standard deviation. It is one of the most commonly occurring distributions for continuous variables. Also, under suitable conditions, other distributions can be approximated by the Normal. Unfortunately, these approximations are often used even if the required conditions are not met!

Related questions

It may be or may not be; however a normal distribution is unimodal.

Yes it is.

No. There are many symmetrical distributions that are not Normal. A simple one is the uniform distribution:

No, not all distributions are symmetrical, and not all distributions have a single peak.

No. There are many other distributions, including discrete ones, that are symmetrical.

No, the normal distribution is strictly unimodal.

It is not necessary that all symetric distribution may be normal.

Unimodal is having a normal disturbution. The mean, median, and mode are all a the center. When looking at a graph, there is one maximum.

Bell-shaped, unimodal, symmetric

Don't know what "this" is, but all symmetric distributions are not normal. There are many distributions, discrete and continuous that are not normal. The uniform or binomial distributions are examples of discrete symmetric distibutions that are not normal. The uniform and the beta distribution with equal parameters are examples of a continuous distribution that is not normal. The uniform distribution can be discrete or continuous.

I think yes or no

The three are different measures of central tendency. None of them are substitutes for the other and, except in symmetric unimodal distributions, none of them can be used to estimate another.

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