The quartile deviation of Normal Distribution is

Normal distribution is a bell-shaped curve that represents the distribution of a set of data which is symmetrical and centered around the mean.

 Key Points In a normal distribution, the mean, median, and mode are all equal.

Quartile deviation is a measure of dispersion that indicates the spread of a distribution relative to the interquartile range (IQR).

In a normal distribution, the quartile deviation is equal to two-thirds of the standard deviation.

To calculate the quartile deviation of a normal distribution, we need to know the standard deviation of the distribution.

From the given information, we know that the normal distribution has a mean of 0 and a standard deviation of 1 (since it is a standard normal distribution).

The quartile deviation is calculated as follows:

Quartile deviation = (Q3 - Q1) / 2

where Q3 and Q1 are the upper and lower quartiles, respectively.

Using the properties of the normal distribution, we can find the z-scores that correspond to the upper and lower quartiles:

Q3 = 0.6745 (since 75% of the data falls below this z-score)

Q1 = -0.6745 (since 25% of the data falls below this z-score)

Substituting these values into the quartile deviation formula,

we get: Quartile deviation = (0.6745 - (-0.6745)) / 2 = 1.349 = 2/3 (rounded to the nearest hundredth).

Therefore, the quartile deviation of the normal distribution is 2/3.