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Which measures of dispersions is not affected by the presence of extreme observations?
- a)Range
- b)Mean deviation
- c)Standard deviation
- d)Quartile deviation
Correct answer is option 'D'. Can you explain this answer?
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Which measures of dispersions is not affected by the presence of extre...
The first variety may be preferred since it is more consistent in yield performance. From the above example, it is obvious that a measure of central tendency alone is not sufficient to describe a frequency distribution. In addition to it we should have a measure of scatterness of observations. The scatterness or variation of observations from their average is called the dispersion. There are different measures of dispersion like the range, the quartile deviation, the mean deviation and the standard deviation.
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Which measures of dispersions is not affected by the presence of extre...
Measures of Dispersion Not Affected by Extreme Observations
Measures of dispersion are used to measure the amount of variability or spread in a data set. These measures include range, mean deviation, standard deviation, and quartile deviation. However, extreme observations or outliers in a data set can skew the results of some measures of dispersion. The measure of dispersion that is not affected by the presence of extreme observations is the quartile deviation.
Quartile Deviation
Quartile deviation is a measure of dispersion that uses quartiles to measure the spread of a data set. Quartiles divide a data set into four equal parts, with each part representing 25% of the data. The quartiles are represented by Q1, Q2, and Q3. Q2 is the median, which divides the data set into two equal parts.
To calculate the quartile deviation, first, find the difference between Q3 and Q1. Then, divide that difference by 2. The result is the quartile deviation.
Advantages of Quartile Deviation
The quartile deviation is not affected by the presence of extreme observations or outliers in a data set. This is because quartiles are based on the rank of the data, not the actual values. As a result, quartile deviation is a more robust measure of dispersion than other measures, such as range and standard deviation.
Conclusion
In conclusion, quartile deviation is a measure of dispersion that is not affected by the presence of extreme observations or outliers in a data set. Quartile deviation is a more robust measure of dispersion than other measures, such as range and standard deviation.
Measures of dispersion are used to measure the amount of variability or spread in a data set. These measures include range, mean deviation, standard deviation, and quartile deviation. However, extreme observations or outliers in a data set can skew the results of some measures of dispersion. The measure of dispersion that is not affected by the presence of extreme observations is the quartile deviation.
Quartile Deviation
Quartile deviation is a measure of dispersion that uses quartiles to measure the spread of a data set. Quartiles divide a data set into four equal parts, with each part representing 25% of the data. The quartiles are represented by Q1, Q2, and Q3. Q2 is the median, which divides the data set into two equal parts.
To calculate the quartile deviation, first, find the difference between Q3 and Q1. Then, divide that difference by 2. The result is the quartile deviation.
Advantages of Quartile Deviation
The quartile deviation is not affected by the presence of extreme observations or outliers in a data set. This is because quartiles are based on the rank of the data, not the actual values. As a result, quartile deviation is a more robust measure of dispersion than other measures, such as range and standard deviation.
Conclusion
In conclusion, quartile deviation is a measure of dispersion that is not affected by the presence of extreme observations or outliers in a data set. Quartile deviation is a more robust measure of dispersion than other measures, such as range and standard deviation.
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Which measures of dispersions is not affected by the presence of extreme observations?a)Rangeb)Mean deviationc)Standard deviationd)Quartile deviationCorrect answer is option 'D'. Can you explain this answer?
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Which measures of dispersions is not affected by the presence of extreme observations?a)Rangeb)Mean deviationc)Standard deviationd)Quartile deviationCorrect answer is option 'D'. Can you explain this answer? for CA Foundation 2024 is part of CA Foundation preparation. The Question and answers have been prepared according to the CA Foundation exam syllabus. Information about Which measures of dispersions is not affected by the presence of extreme observations?a)Rangeb)Mean deviationc)Standard deviationd)Quartile deviationCorrect answer is option 'D'. Can you explain this answer? covers all topics & solutions for CA Foundation 2024 Exam. Find important definitions, questions, meanings, examples, exercises and tests below for Which measures of dispersions is not affected by the presence of extreme observations?a)Rangeb)Mean deviationc)Standard deviationd)Quartile deviationCorrect answer is option 'D'. Can you explain this answer?.
Which measures of dispersions is not affected by the presence of extreme observations?a)Rangeb)Mean deviationc)Standard deviationd)Quartile deviationCorrect answer is option 'D'. Can you explain this answer? for CA Foundation 2024 is part of CA Foundation preparation. The Question and answers have been prepared according to the CA Foundation exam syllabus. Information about Which measures of dispersions is not affected by the presence of extreme observations?a)Rangeb)Mean deviationc)Standard deviationd)Quartile deviationCorrect answer is option 'D'. Can you explain this answer? covers all topics & solutions for CA Foundation 2024 Exam. Find important definitions, questions, meanings, examples, exercises and tests below for Which measures of dispersions is not affected by the presence of extreme observations?a)Rangeb)Mean deviationc)Standard deviationd)Quartile deviationCorrect answer is option 'D'. Can you explain this answer?.
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