Best Answer

Yes- the highest probability value is the mode. Let me clarify this answer:

For a probability mass function for a discrete variables, the mode is the value with the highest probability as shown on the y axis. For a probability density function for continuous variables, the mode is the value with the highest probability density as shown on the y-axis.

Q: The mode is the largest value in a symmetric distribution?

Write your answer...

Submit

Still have questions?

Continue Learning about Math & Arithmetic

The mode of the Pareto distribution is its lowest value.

The mode is the most probable value. Often, you determine the mode by plotting the experimental probability distribution, and finding the peak value. The mode is not necessarily the same as the mean nor the median, unless the distribution is symmetrical.

You may be most familiar with the normal distribution (the Bell-shaped curve). The mean, mode and median of this distribution are all the same because it is symmetric. If, however, you take a sample from a distribution that is asymmetric in some way then the mean, mode and median will differ. You would need to decide which of these more effectively characterises the population. Then you would compute that descriptive statistic.

(10, 15, 15, 15, 20) The answer above displays a sample in which the sample mean, sample median and sample mode assume the same value. If you were asking about populations, then the population mean, population median and population mode are the same whenever the probability density function for the population is symmetric. For example, the normal probability density function is symmetric, the t and uniform density functions are symmetric. Many are.

Yes, mode equals median in a normal distribution.

Related questions

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.

Mean

All equal.

They are all equal . . . they are the same.(In an asymmetric distribution they are not equal.)

In a symmetric distribution, the mean and the median are the same. Otherwise there is no relation. In symmetric distributions with only one mode, the mode will coincide with the mean and median, but otherwise there is no relation.

They are all the same.

It is the expected value of the distribution. It also happens to be the mode and median.It is the expected value of the distribution. It also happens to be the mode and median.It is the expected value of the distribution. It also happens to be the mode and median.It is the expected value of the distribution. It also happens to be the mode and median.

Not necessarily.

The mode of the Pareto distribution is its lowest value.

The mode is the most probable value. Often, you determine the mode by plotting the experimental probability distribution, and finding the peak value. The mode is not necessarily the same as the mean nor the median, unless the distribution is symmetrical.

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).

No. Normal distribution is uni-modal, specifically with the mean, mode, and median at the same value.