24
No. The binomial distribution (discrete) or uniform distribution (discrete or continuous) are symmetrical but they are not normal. There are others.
They are all equal . . . they are the same.(In an asymmetric distribution they are not equal.)
All equal.
It is not necessary that all symetric distribution may be normal.
No. Normal distribution is a special case of distribution.
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.
No. The binomial distribution (discrete) or uniform distribution (discrete or continuous) are symmetrical but they are not normal. There are others.
They are all the same.
No, not all distributions are symmetrical, and not all distributions have a single peak.
The data from a normal distribution are symmetric about its mean, not about zero. There is, therefore nothing strange about all the values being negative.
They are all equal . . . they are the same.(In an asymmetric distribution they are not equal.)
All equal.
If the distribution of heights were symmetric then it would be 1/2 but the distribution is not at all likely to be symmetric. There will by many young trees of varying heights whereas the mature trees are likely to reach similar heights. The distribution is, therefore, likely to be negatively skewed, which means that the probability is greater than 1/2.
It is a type of light distribution. Symmetric distribution would be like normal down lighting with distribution to cover all surfaces. Asymmeteric distribution would be a down light that has distribution both down and to one side to cover a specific surface or object. Like a spot light or a wall wash fixture.
It is not necessary that all symetric distribution may be normal.
No. Normal distribution is a special case of distribution.
Yes. Normal (or Gaussian) distribution are parametric distributions and they are defined by two parameters: the mean and the variance (square of standard deviation). Each pair of these parameters gives rise to a different normal distribution. However, they can all be "re-parametrised" to the standard normal distribution using z-transformations. The standard normal distribution has mean 0 and variance 1.