Question-26:  How range is affected by outlier?

Answer: Let’s see below data

                1 1 2 2 2 2 5 5 à Range = 5-1=4

                 1 1 2 2 2 2 5 10 à Range = 10-1=9

In the second dataset only one outlier exists and affect the range heavily. Hence, range can only tell us how apart both upper and lower value. But does not tell about all other data between the range.

Question-27: Is there a way by which we can reduce the effect of outlier in range?

Answer: Yes, we need to ignore outliers by creating a mini range.

Question-28: Can you please give some example of consistently removing outliers across all the dataset?

Answer: Yes, using the quartiles.

Question-29: What are the quartiles?

Answer: Let’s say we have following dataset

1 2 3 4 5 10 4 4 4 2 1 2 1 5 4 5

Arrange them in ascending order

                1 1 1 2 2 2 3 4 4 4 4 4 5 5 5 10

Now divide them in 4 equal parts

1 1 1 2                   2 2 3 4                   4 4 4 4                   5 5 5 10

The value which split the data into equal size or chunks are known as quartiles, because data is broken by quarter.

Question-30: What are the upper and lower quartile?

Answer:  Sometime people may get confused with Q1, Q2 and Q3. Q is lower quartile; this is a first quarter. But Q3 represent highest quartile.

1 1 1 2 Q1 2 2 3 4 Q2 4 4 4 4 Q3 5 5 5 10