It may be or may not be; however a normal distribution is unimodal.
No, the normal distribution is strictly unimodal.
Your distribution is unimodal and symmetrical.
A uniform distribution.A uniform distribution.A uniform distribution.A uniform distribution.
Please consider the probability density function graphs for the beta distribution, given in the link. For alpha=beta=2, the density is unimodal, which is to say, it has a single maximum. In contrast, for alpha=beta=0.5, the density is bimodal; it has two maxima.
It may be or may not be; however a normal distribution is unimodal.
No they are not the same in a unimodal symmetrical distribution and they will never be
No, it is in general not true - for example for uniform distribution on [0,1] every number in the interval is a mode, but the mean is 1/2. The correct answer would be that a symmetric unimodal distribution has one mode equal to the mean (but may have modes elsewhere).
Yes it is.
No, the normal distribution is strictly unimodal.
No. Normal distribution is a special case of distribution.
The median and mode.
Your distribution is unimodal and symmetrical.
A uniform distribution.A uniform distribution.A uniform distribution.A uniform distribution.
If the distribution is not symmetric, the mean will be different from the median. A negatively skewed distribution will have a mean hat is smaller than the median, provided it is unimodal.
Please consider the probability density function graphs for the beta distribution, given in the link. For alpha=beta=2, the density is unimodal, which is to say, it has a single maximum. In contrast, for alpha=beta=0.5, the density is bimodal; it has two maxima.
Yes, the uniform probability distribution is symmetric about the mode. Draw the sketch of the uniform probability distribution. If we say that the distribution is uniform, then we obtain the same constant for the continuous variable. * * * * * The uniform probability distribution is one in which the probability is the same throughout its domain, as stated above. By definition, then, there can be no value (or sub-domain) for which the probability is greater than elsewhere. In other words, a uniform probability distribution has no mode. The mode does not exist. The distribution cannot, therefore, be symmetric about something that does not exist.