Why do we prefer standard deviation to quartile deviation as a measure of dispersion?

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Dispersion is a statistical concept that quantifies the spread or variability of data points within a dataset. It helps to understand the distribution and pattern of data values, allowing us to make informed decisions and draw meaningful conclusions. Two common measures of dispersion are Standard Deviation and Quartile Deviation. While both provide insights into the spread of data, statisticians and analysts often prefer standard deviation over quartile deviation due to several reasons. This essay explores the advantages of using standard deviation as a measure of dispersion compared to quartile deviation.

Standard Deviation:

Standard deviation is a widely used measure of dispersion that provides a comprehensive view of the variability in a dataset. It calculates the average distance of each data point from the mean of the data. In other words, standard deviation measures the typical deviation of data values from their mean, making it sensitive to even small variations.

Advantages of Standard Deviation:

1. Reflects the entire dataset: Standard deviation considers every data point in the dataset while calculating the spread. It takes into account both the direction and magnitude of deviations from the mean. This comprehensive approach ensures that no information is ignored, making it a robust measure to summarize dispersion.

2. Efficient for further analysis: Standard deviation is mathematically convenient and has many desirable properties, especially when dealing with continuous distributions. Its mathematical characteristics facilitate various inferential and predictive analyses, making __ ___________ ________ _____________ __________ __________ _______ ______ _______ _________ ___________ _____________ ___.
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Degree : BACHELOR DEGREE PROGRAMMES
Course Name : BACHELOR IN COMMERCE CHOICE BASED CREDIT SYSTEM
Course Code : B.Com(G) CBCS
Subject Name : BUSINESS MATHEMATICS AND STATISTICS
Subject Code : BCOC 134
Year : 2022 2023