• 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).
  • Advantages:
    • 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.
  • Advantages:
    • 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.
  • Advantages:
    • 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

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