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Understanding
Variability:
Range and Mean
Deviation
 What is Variability?
 -Variability is a fundamental concept in statistics that plays a vital
role in understanding and interpreting data. It also refers to the
extent to which data points in a data set differ from each other.
It captures the differences or deviations between individual data
points, providing insights into the range of values present.
Therefore, understanding variability is essential for making
informed decisions, drawing accurate conclusions, and
uncovering meaningful relationships within the data.
 Measure of Variability
 A measure of variability, also known as a measure of dispersion,
is a statistical metric that quantifies the spread or dispersion of a
set of data points. It is an important consideration when the
properties of the data set are being investigated because it tells
how much scores in a data set vary from one another. Measure
of variability are crucial in data analysis as they help in
understanding the diversity, range, and consistency of the data.
 Common measures of variability:
 Range - The range is the full distance between the lowest and highest
scores in distribution. It is the easiest and the quickest to compute. It can
be classified into two: the exclusive range and the inclusive range. The
exclusive range is the difference between the highest score (HS) and the
lowest score (LS) in the distribution, and its formula is ( HS - LS). The
inclusive range is the difference between the highest score and lowest
score plus one (HS - LS + 1).
o Example of solving an inclusive range
and exclusive range :
-For example, you will consider a data set of score which have a
no. of 3,5,7,9,11. To calculate the inclusive range, the formula will
be: Inclusive range = 11(HS) – 3(LW) + 1 = 9, therefore by using the
formula you will get the answer for inclusive range which is 9.
While the formula for exclusive range is HS-LW. To calculate
formula for exclusive range, it will be shown or solved as: exclusive
range = 11 (HS) – 3(LS) = 8, and that will be your no. of score or
the amount for exclusive range.
Mean deviation
- Mean deviation is a measure of dispersion or variability that
gives a rough estimate of the distances of the individual scores
from the mean of the scores. It is the average of the absolute
deviations of the scores from the mean. In mathematical form it is
 To calculate the mean deviation, you typically
follow these steps:
1. Find the mean of the data set.
2. Calculate the absolute difference between each data point and
the mean.
3. Find the average of these absolute difference.
Example 1: Calculate the mean deviation of the following set of scores: 2, 4, 4,
7, 8, 9, 10, 12.
Solution: The mean of the scores is 56/8=7. The mean deviation can be
calculated as follows:
 Here is the step by step process for you to understand more:
1. Find the mean of the data set:
-Mean = (2+4+4+7+8+9+10+12) / 8
Mean = 56/8 = 7
2. Calculate the absolute difference between each data point and the mean:
(2-7= 5), (4-7= 3), ( 4-7= 3), (7-7= 0), (8-7= 1), (9-7= 2), (10-7=3), (12-7= 5).
3. Find the sum of the absolute difference:
-Sum of absolute differences = 5+3+3+0+1+2+3+5
Sum of absolute differences = 22
4. Calculate the mean deviation:
-Mean Deviation = Sum of absolute differences / Number of data points
Mean deviation = 22 / 8
Mean Deviation= 2.75
Therefore, the average distance of the scores from the mean is 2.75.
Understanding Variability Range and Mean Research

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Understanding Variability Range and Mean Research

  • 2.  What is Variability?  -Variability is a fundamental concept in statistics that plays a vital role in understanding and interpreting data. It also refers to the extent to which data points in a data set differ from each other. It captures the differences or deviations between individual data points, providing insights into the range of values present. Therefore, understanding variability is essential for making informed decisions, drawing accurate conclusions, and uncovering meaningful relationships within the data.
  • 3.  Measure of Variability  A measure of variability, also known as a measure of dispersion, is a statistical metric that quantifies the spread or dispersion of a set of data points. It is an important consideration when the properties of the data set are being investigated because it tells how much scores in a data set vary from one another. Measure of variability are crucial in data analysis as they help in understanding the diversity, range, and consistency of the data.
  • 4.  Common measures of variability:  Range - The range is the full distance between the lowest and highest scores in distribution. It is the easiest and the quickest to compute. It can be classified into two: the exclusive range and the inclusive range. The exclusive range is the difference between the highest score (HS) and the lowest score (LS) in the distribution, and its formula is ( HS - LS). The inclusive range is the difference between the highest score and lowest score plus one (HS - LS + 1).
  • 5. o Example of solving an inclusive range and exclusive range : -For example, you will consider a data set of score which have a no. of 3,5,7,9,11. To calculate the inclusive range, the formula will be: Inclusive range = 11(HS) – 3(LW) + 1 = 9, therefore by using the formula you will get the answer for inclusive range which is 9. While the formula for exclusive range is HS-LW. To calculate formula for exclusive range, it will be shown or solved as: exclusive range = 11 (HS) – 3(LS) = 8, and that will be your no. of score or the amount for exclusive range.
  • 6. Mean deviation - Mean deviation is a measure of dispersion or variability that gives a rough estimate of the distances of the individual scores from the mean of the scores. It is the average of the absolute deviations of the scores from the mean. In mathematical form it is
  • 7.  To calculate the mean deviation, you typically follow these steps: 1. Find the mean of the data set. 2. Calculate the absolute difference between each data point and the mean. 3. Find the average of these absolute difference. Example 1: Calculate the mean deviation of the following set of scores: 2, 4, 4, 7, 8, 9, 10, 12. Solution: The mean of the scores is 56/8=7. The mean deviation can be calculated as follows:
  • 8.  Here is the step by step process for you to understand more: 1. Find the mean of the data set: -Mean = (2+4+4+7+8+9+10+12) / 8 Mean = 56/8 = 7 2. Calculate the absolute difference between each data point and the mean: (2-7= 5), (4-7= 3), ( 4-7= 3), (7-7= 0), (8-7= 1), (9-7= 2), (10-7=3), (12-7= 5). 3. Find the sum of the absolute difference: -Sum of absolute differences = 5+3+3+0+1+2+3+5 Sum of absolute differences = 22 4. Calculate the mean deviation: -Mean Deviation = Sum of absolute differences / Number of data points Mean deviation = 22 / 8 Mean Deviation= 2.75 Therefore, the average distance of the scores from the mean is 2.75.