Both classes are modal classes.
If you have a set of individual observations, the mode is the observation that occurs the most often.However, with very large sets, you may wish to group the data into classes. In that case, the class with the largest frequency is the modal class.The modal class need not contain the mode. Also, the modal class depends on how the classes are defined.
The distribution is bi-modal. That is to say both the numbers are modes.
There is no modal value.
It is quite possible for there to be no mode. A sample from a continuous distribution may have a modal class but is very unlikely to have a mode.
It is simply a distribution which has two modal classes: you cannot convert two of them into a mode.
Then the collected data is bi-modal
No. Normal distribution is uni-modal, specifically with the mean, mode, and median at the same value.
Both classes are modal classes.
If you have a set of individual observations, the mode is the observation that occurs the most often.However, with very large sets, you may wish to group the data into classes. In that case, the class with the largest frequency is the modal class.The modal class need not contain the mode. Also, the modal class depends on how the classes are defined.
The distribution is bi-modal. That is to say both the numbers are modes.
It is often claimed that height is bi-modal because there will be one modal height for men and one for women. But unless there are exactly the same number of men and of women in the modal class, both cannot be modes. Consequently, this attribute really has only one mode. The same applies to other characteristics.
There is no modal value.
the modal/mode in maths is like the average, getting it by adding all pieces of data and dividing on how many there are
If there are more than one class intervals which have the same frequency (equally qualifying to be the mode class) then both of the classes will be the mode class. this is called bimodal. However to calculate the mode of grouped data use the following formula Mode = L + [ (F - F1) / { (F - F1) + (F - F2) } ] * h where L = Lower limit of the modal class F = Frequency of the modal class F1 = Frequency of the class immediately previous of modal class F2 = Frequency of the class immediate next of modal class h = Range of the modal class (higher limit - lower limit) this is what i found out after reading books and understanding them. Please correct me if i am wrong. Thanks, Salman Ahmad
It is quite possible for there to be no mode. A sample from a continuous distribution may have a modal class but is very unlikely to have a mode.
A single number, such as 3456, has only one mode and that is itself.