**Mode in statistics :**

Mode is one of the measures of central tendency which can be defined as follows.

For a given set of observations, mode may be defined as the value that occurs the maximum number of times.

Thus, mode is that value which has the maximum concentration of the observations around it. This can also be described as the most common value with which, even, a layman may be familiar with.

Thus, if the observations are 5, 3, 8, 9, 5 and 6, then Mode (Mo) = 5 as it occurs twice and all the other observations occur just once.

The definition for mode also leaves scope for more than one mode. Thus sometimes we may come across a distribution having more than one mode. Such a distribution is known as a multi-modal distribution. Bi-modal distribution is one having two modes.

Furthermore, it also appears from the definition that mode is not always defined. As an example,

If the marks of 5 students are 50, 60, 35, 40, 56, there is no modal mark as all the observations occur once i.e. the same number of times.

We may consider the following formula for computing mode from a grouped frequency distribution:

Where,

l₁ = LCB of the modal class

f₀ = frequency of the modal class

f₋₁ = frequency of the pre modal class

f₁ = frequency of the post modal class

C = class length of the modal class

**Compute the mode for the following distribution**

**Solution :**

**Computation of mode**

For the given data, the formula to find mode is given by

Going through the frequency column, we note that the highest frequency i.e. f₀ is 82.

So we have,

f₋₁ = 58

f₁ = 65

Also, the modal class i.e. the class against the highest frequency is 410 - 419

Thus,

l₁ = LCB = 409.50

C = 429.50 - 409.50 = 20

C = 429.50 – 409.50 = 20

Plugging these values in the above formula, we get

Mode = 409.50 + [ (82-58) / (2x52 - 58 - 65) ] x 20

Mode = 409.50 + 11.71

**Mode = 421.21**

When it is difficult to compute mode from a grouped frequency distribution, we may consider the following empirical relationship between mean, median and mode:

**Mean - Mode = 3(Mean - Median)**

or

**Mode = 3 x median - 2 x mean**

The above result holds for holds for a moderately skewed distribution.

We also note that if y = a + bx, then we have

**Mode of "y" = a + b (Mode of "x") **

For example, if y = 2 + 1.50x and mode of x is 15, then the mode of y is given by

Mode of "y" = 2 + 1.50(Mode of "x")

Mode of "y" = 2 + 1.50x15

Mode of "y" = 2 + 22.50

**Mode of "y" = 24.50**

1) Although mode is the most popular measure of central tendency, there are cases when mode remains undefined.

2) Unlike mean, it has no mathematical property.

3) Mode is affected by sampling fluctuations.

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