Range - Measures of Dispersion, Business Mathematics & Statistics

# Range - Measures of Dispersion, Business Mathematics & Statistics Video Lecture - Business Mathematics and Statistics - B Com

115 videos|142 docs

## FAQs on Range - Measures of Dispersion, Business Mathematics & Statistics Video Lecture - Business Mathematics and Statistics - B Com

 1. What is the range in statistics?
Ans. The range is a measure of dispersion in statistics that represents the difference between the largest and smallest values in a dataset. It provides a simple way to understand the spread of data by indicating the extent of variation from the lowest to the highest value.
 2. How is the range calculated?
Ans. To calculate the range, you subtract the smallest value from the largest value in the dataset. For example, if you have a dataset with values 5, 8, 12, 15, and 20, the range would be 20 - 5 = 15.
 3. What are the limitations of using range as a measure of dispersion?
Ans. While range provides a basic understanding of the spread of data, it has limitations. For instance, it only considers the extreme values and ignores the other values in the dataset. Additionally, it does not account for the distribution of values within the range, making it sensitive to outliers and not capturing the overall variability accurately.
 4. Can the range be negative?
Ans. No, the range cannot be negative. By definition, the range represents the difference between the largest and smallest values, and a negative range would imply that the smallest value is larger than the largest value, which is not possible.
 5. How does the range differ from other measures of dispersion, such as standard deviation?
Ans. The range and standard deviation are both measures of dispersion, but they capture different aspects. While the range provides a simple understanding of the spread by focusing on the extreme values, the standard deviation takes into account all the values in the dataset and provides a more comprehensive measure of variability. The standard deviation considers the differences between each value and the mean, allowing for a more nuanced interpretation of the data's spread.

115 videos|142 docs
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