No, the normal distribution is strictly unimodal.
By specifying the centre and standard deviation of the distribution but also mentioning the fact that it is bimodal and identifying the modes.
This could be a bimodal. There are many other factors that would have to be taken into account as well.
A bimodal distribution.
Nothing. You simply have a distribution that is bimodal. You report both modes.
No, the normal distribution is strictly unimodal.
Bimodal Distribution
By specifying the centre and standard deviation of the distribution but also mentioning the fact that it is bimodal and identifying the modes.
The distribution is bimodal. That is all there is to it.
No. A distribution may be non-skewed and bimodal or skewed and bimodal. Bimodal means that the distribution has two modes, or two local maxima on the curve. Visually, one can see two peaks on the distribution curve. Mixture problems (combination of two random variables with different modes) can produce bimodal curves. See: http://en.wikipedia.org/wiki/Bimodal_distribution A distribution is skewed when the mean and median are different values. A distribution is negatively skewed when the mean is less than the median and positively skewed if the mean is greater than the median. See: http://en.wikipedia.org/wiki/Skewness
This could be a bimodal. There are many other factors that would have to be taken into account as well.
A bimodality is a bimodal condition - a distribution which has two modes.
A bimodal distribution.
A distribution with 2 modes is said to be bimodal.
The bimodal distribution of elevations on Earth's surface is due to the presence of both ocean basins and continental landmasses. The ocean basins are generally lower in elevation, while the continental landmasses have higher elevations, resulting in the bimodal distribution commonly observed.
Nothing. You simply have a distribution that is bimodal. You report both modes.
In statistics, a distribution curve that has two peaks is referred to as bimodal.