Measure of dispersion considering only extreme values is calleda)stand...
Range is the difference between the largest value and the smallest value of a series.
Range = L- S
Here, L= Largest value, S= Smallest value.
No other values of the series are taken into consideration in this case.
View all questions of this test
Measure of dispersion considering only extreme values is calleda)stand...
Range is the difference between the largest value and the smallest value of a series.
Range = L- S
Here, L= Largest value, S= Smallest value.
No other values of the series are taken into consideration in this case.
Measure of dispersion considering only extreme values is calleda)stand...
Understanding Measures of Dispersion
Dispersion refers to the extent to which a distribution varies. It provides insights into the spread of data points in a dataset. Among various measures of dispersion, some focus on the overall distribution, while others consider extreme values.
What is the Range?
- The range is defined as the difference between the maximum and minimum values in a dataset.
- It captures only the extreme values, ignoring other data points.
- Formula: Range = Maximum Value - Minimum Value
Why is Range Important?
- It provides a quick assessment of variability within a dataset.
- Useful in understanding the potential spread of data, especially in simple datasets.
- Helps to identify outliers by showcasing the extremes.
Comparison with Other Measures of Dispersion
- Standard Deviation: Measures how much individual data points deviate from the mean. It considers all values, not just extremes.
- Mean Deviation: Evaluates the average of absolute deviations from the mean, again incorporating all data points.
- Quartile Deviation: Focuses on the middle 50% of data, measuring the spread between the first and third quartiles.
Conclusion
In summary, the correct answer to the question is option 'C', which is the range. The range is the only measure of dispersion that specifically emphasizes the extreme values in a dataset, making it distinct from other measures that take all data points into account. This characteristic makes the range particularly valuable when assessing the potential variability and outliers in a dataset.
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