How to Measures of Dispersion?
Measures of dispersion are non-negative real numbers that measure the dispersion of data about a central value. In this step-by-step guide, you will learn more about the most commonly used measures of dispersion.
Related Topics
A step-by-step guide to measures of dispersion
Measures of dispersion can be defined as positive real numbers that measure the degree of homogeneity or heterogeneity of the given data.
A measure of dispersion will have a value of \(0\) if the data points in a data set are the same. However, as the variability of the data increases, so does the value of dispersion measures.
Types of measures of dispersion
The measures of dispersion can be classified into two general categories. These are absolute measures of dispersion and relative measures of dispersion.
Range, variance, standard deviation, and average deviation are included in the category of absolute deviation measures.
These measures have the same unit as the data being examined. Coefficients of dispersion are relative measures of deviation. Such dispersion measures are always dimensionless.
Absolute measures of dispersion
The most common absolute measures of deviation are:
Range: Given a set of data, the range can be defined as the difference between the maximum and the minimum value.
Variance: The average squared deviation from the mean of the given data set is known as a variance. This measure of dispersion examines the spread of the data about the mean. The formula of variance is:
\(\color{blue}{σ^2=\frac{1}{n}\sum _{i=1}^n\:\left(x_i-x\:̅\:\right)^2\:}\)
where \(n\) is the number of observations and \(x¯\) is the mean.
Standard deviation: It shows the square root of the variance of the standard deviation. Therefore, the standard deviation also measures the variation of the data about the mean. The formula of standard deviation is:
\(\color{blue}{σ=\sqrt{σ^2}}\)
Mean Deviation: Mean deviation shows the mean of the data’s absolute deviation about the central points. These center points can be the mean, median, or mode. The formula for mean deviation is:
\(\color{blue}{\frac{1}{n}\:\sum _{i=1}^n|x_i-x\:̅\:|\:}\)
Where \(x¯\) is the central value and denotes the mean, median, or mode.
Measures of Dispersion – Example 1:
Find the population standard deviation of the data set. \({1, 4, 8, 7, 14}\)
Solution: Standard deviation is a measure of dispersion given by the formula \(σ=\sqrt{σ^2}\):
\(x¯=\frac{1+4+8+7+14}{5}=6.8\)
\(σ^2=\frac{\left(1\:-\:6.8\right)^2+\left(4\:-\:6.8\right)^2+\left(8\:-\:6.8\right)^2+\left(7\:-\:6.8\right)^2+\left(14\:-\:6.8\right)^2}{5}=18.96\)
\(σ=\sqrt{18.96}= 4.35\)
Related to This Article
More math articles
- Prepare for the SAT Math: The Right Combination of Hard Work and Time Management
- The Secret Decoder Ring of Proportional Relationships: How to Find The Constant of Proportionality
- Full-Length TSI Math Practice Test
- 5th Grade Wisconsin Forward Math Worksheets: FREE & Printable
- Top 10 SIFT Math Practice Questions
- Top 10 SHSAT Prep Books (Our 2023 Favorite Picks)
- 7th Grade NYSE Math FREE Sample Practice Questions
- The Best ASTB Math Worksheets: FREE & Printable
- A Step into The World of Calculus: Rules of Differentiation
- Intelligent Math Puzzle – Challenge 83
What people say about "How to Measures of Dispersion? - Effortless Math: We Help Students Learn to LOVE Mathematics"?
No one replied yet.