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Page 1 CPT Section D Quantitative Aptitude Chapter 11 Dr.R.B.Tiwari Page 2 CPT Section D Quantitative Aptitude Chapter 11 Dr.R.B.Tiwari MCQ’s Page 3 CPT Section D Quantitative Aptitude Chapter 11 Dr.R.B.Tiwari MCQ’s (a) Standard deviation (b) Mean deviation (c) Quartile deviation (d) All these measures Answer: (c) Quartile Deviation The appropriate measure of dispersion for open-end classification is Page 4 CPT Section D Quantitative Aptitude Chapter 11 Dr.R.B.Tiwari MCQ’s (a) Standard deviation (b) Mean deviation (c) Quartile deviation (d) All these measures Answer: (c) Quartile Deviation The appropriate measure of dispersion for open-end classification is (a) Range (b) Mean deviation (c) Standard deviation (d) all these above Answer: (b) Mean deviation Which measure of dispersion includes absolute deviations. Page 5 CPT Section D Quantitative Aptitude Chapter 11 Dr.R.B.Tiwari MCQ’s (a) Standard deviation (b) Mean deviation (c) Quartile deviation (d) All these measures Answer: (c) Quartile Deviation The appropriate measure of dispersion for open-end classification is (a) Range (b) Mean deviation (c) Standard deviation (d) all these above Answer: (b) Mean deviation Which measure of dispersion includes absolute deviations. (a) Range (b) Mean deviation (c) Standard deviation (d) all these above Answer: (c) Standard deviation A change of origin has no impact onRead More
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FAQs on PPT - Measure of Dispersion - Quantitative Aptitude for CA Foundation
| 1. What is a measure of dispersion? |  |
Ans. A measure of dispersion is a statistical term that quantifies the extent to which data points in a dataset vary from the mean. It provides insights into the spread or variability of the data.
| 2. Why is it important to measure dispersion in data? | |
Ans. Measuring dispersion is important as it helps in understanding the range of values within a dataset. It provides information about the spread of data points, which is crucial for making accurate inferences and drawing meaningful conclusions from the data.
| 3. What are the commonly used measures of dispersion? | |
Ans. There are several commonly used measures of dispersion, including the range, variance, and standard deviation. The range is the simplest measure and represents the difference between the maximum and minimum values in the dataset. Variance and standard deviation, on the other hand, provide a more comprehensive understanding of the data's spread by considering the deviation of each data point from the mean.
| 4. How is variance calculated as a measure of dispersion? | |
Ans. Variance is calculated by taking the average of the squared deviations of each data point from the mean. It involves three main steps: (1) Calculate the mean of the dataset, (2) Subtract the mean from each data point and square the result, (3) Calculate the average of the squared deviations. The variance provides a measure of the average squared distance between each data point and the mean.
| 5. What does a high or low measure of dispersion indicate? | |
Ans. A high measure of dispersion indicates that the data points in the dataset are widely spread out, indicating greater variability. On the other hand, a low measure of dispersion suggests that the data points are closely clustered around the mean, indicating less variability. Understanding the level of dispersion is essential for analyzing the data accurately and making informed decisions.
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