The modes of a probability density function might be defined as the (countable) set of points in the domain of the function for which the function achieves local maxima. Since the probability density function for the uniform distribution is constant by definition it has no local maxima, hence no modes. Hence, it cannot be bimodal.
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
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).
Two modes is termed bimodal. It is OK to have two modes; both values will be the modes.
The result is a collection of grouped data.
A distribution with two modes.
A distribution with 2 modes is said to be bimodal.
Nothing. You simply have a distribution that is bimodal. You report both modes.
The data values with the highest frequency, gives the peak of the distribution graph.
A bimodality is a bimodal condition - a distribution which has two modes.
A 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 basic methods meant for distribution usually affect the type of advertising chosen for them. Traditional methods of distribution work well with traditional advertising modes such as flyers and word of mouth.
The modes of a probability density function might be defined as the (countable) set of points in the domain of the function for which the function achieves local maxima. Since the probability density function for the uniform distribution is constant by definition it has no local maxima, hence no modes. Hence, it cannot be bimodal.
A society having or involving several modes.
The distribution is bi-modal. That is to say both the numbers are modes.
Yes, as well as several other modes. They actually knew a lot about harmony/theory when it came to songwriting.