• Measures of dispersion are an essential tool in market research that allows businesses to analyze the spread of data around the central value.
• Dispersion measures help companies to make informed decisions based on data variability.
• In this article, we will discuss the most common measures of dispersion in market research, and provide an example data set for calculations.

#### Example Data Set:

Let’s consider a hypothetical data set representing the number of units sold by a company over the last 10 quarters:

12, 8, 6, 9, 10, 7, 11, 14, 13, 10

#### Measures of Dispersion:

1. Range:
• Features: The range is the difference between the highest and lowest values in a data set. It provides a quick estimate of data spread.
• Calculation: In our example data set, the range is 8 (14-6).
• Easy and quick to calculate
• Provides an indication of the spread of the data
• Useful for identifying outliers
• Useful for comparing the spread of data sets with different units of measurement
• Drawbacks:
• Range is sensitive to extreme values and outliers
• Does not consider all values in the data set
• Cannot provide information on how values are distributed within the data set
• May not be representative of the variability of the data set
1. Variance:
• Features: Variance measures the average distance of each data point from the mean of the data set. It is more precise than the range.
• Calculation: Using our example data set, the variance is 6.61.
• Provides a more accurate measure of the spread of the data
• Takes into account all values in the data set
• Useful for analyzing how the data is distributed
• Useful for comparing the spread of data sets with the same units of measurement
• Drawbacks:
• Variance is sensitive to extreme values and outliers
• Requires more complex calculations than the range
• Cannot be used to compare the spread of data sets with different units of measurement
• May not be representative of the variability of the data set if the data is not normally distributed
1. Standard Deviation:
• Features: The standard deviation is the square root of the variance and provides a measure of the average deviation of each data point from the mean of the data set.
• Calculation: Using our example data set, the standard deviation is 2.57.
• Provides a more intuitive measure of the spread of the data than variance
• Takes into account all values in the data set
• Useful for analyzing how the data is distributed
• Useful for comparing the spread of data sets with the same units of measurement
• Drawbacks:
• Sensitive to extreme values and outliers
• Requires more complex calculations than the range
• Cannot be used to compare the spread of data sets with different units of measurement
• May not be representative of the variability of the data set if the data 