What Is Interquartile Range in Statistics?

What Is Interquartile Range in Statistics?
The interquartile range (IQR) is a measure of variability, based on dividing a data set into quartiles. The values that divide each part are called the first, second, and third quartiles; and they are denoted by Q1, Q2, and Q3, respectively. Q1 is the "middle" value in the first half of the rank-ordered data set.

.

Also, how do you find the interquartile range?

Steps:

  1. Step 1: Put the numbers in order.
  2. Step 2: Find the median.
  3. Step 3: Place parentheses around the numbers above and below the median. Not necessary statistically, but it makes Q1 and Q3 easier to spot.
  4. Step 4: Find Q1 and Q3.
  5. Step 5: Subtract Q1 from Q3 to find the interquartile range.

Subsequently, question is, how do you find the interquartile range of a normal distribution? When working with box plots, the IQR is computed by subtracting the first quartile from the third quartile. In a standard normal distribution (with mean 0 and standard deviation 1), the first and third quartiles are located at -0.67448 and +0.67448 respectively. Thus the interquartile range (IQR) is 1.34896.

Beside above, what does the interquartile range tell you?

The IQR tells how spread out the "middle" values are; it can also be used to tell when some of the other values are "too far" from the central value. These "too far away" points are called "outliers", because they "lie outside" the range in which we expect them.

How do you find the interquartile range of an odd number?

Then, divide your data set in half and find the median of both the lower and upper half. If you have an odd amount of numbers, don't include the middle number. Finally, subtract the median of the lower half from the median of the upper half to find the IQR.

Related Question Answers

How do you find the range?

Summary: The range of a set of data is the difference between the highest and lowest values in the set. To find the range, first order the data from least to greatest. Then subtract the smallest value from the largest value in the set.

Why is interquartile range important?

Besides being a less sensitive measure of the spread of a data set, the interquartile range has another important use. Due to its resistance to outliers, the interquartile range is useful in identifying when a value is an outlier.
Marcus Vance
Author

Marcus Vance

Marcus Vance is a cybersecurity auditor and technology writer dedicated to educating the public about online safety, data privacy regulations, enterprise security, and emerging cyber threats.