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Calculating Standard Deviation for Discrete and Continuous Frequency Distributions Video Lecture | Mathematics for GRE Paper II

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FAQs on Calculating Standard Deviation for Discrete and Continuous Frequency Distributions Video Lecture - Mathematics for GRE Paper II

1. How is the standard deviation calculated for a discrete frequency distribution?
Ans. To calculate the standard deviation for a discrete frequency distribution, you need to follow these steps: 1. Calculate the mean of the distribution by multiplying each data value by its respective frequency, summing them up, and then dividing by the total frequency. 2. Subtract the mean from each data value and square the result. 3. Multiply each squared difference by its respective frequency and sum them up. 4. Divide the sum of the squared differences by the total frequency. 5. Take the square root of the result obtained in step 4 to get the standard deviation.
2. How is the standard deviation calculated for a continuous frequency distribution?
Ans. To calculate the standard deviation for a continuous frequency distribution, you need to follow these steps: 1. Calculate the mean of the distribution by multiplying each data value by its respective frequency, summing them up, and then dividing by the total frequency. 2. Subtract the mean from each data value and square the result. 3. Multiply each squared difference by its respective frequency and sum them up. 4. Divide the sum of the squared differences by the total frequency. 5. Take the square root of the result obtained in step 4 to get the standard deviation.
3. What is the importance of calculating the standard deviation in frequency distributions?
Ans. The standard deviation is an essential measure in frequency distributions as it provides information about the dispersion or spread of the data. A higher standard deviation indicates that the data values are more spread out from the mean, while a lower standard deviation suggests that the data values are closely clustered around the mean. By calculating the standard deviation, we can quantify the variability within the data and make comparisons between different distributions.
4. Can the standard deviation be negative?
Ans. No, the standard deviation cannot be negative. It is always a non-negative value or zero. The standard deviation represents the average amount of deviation or dispersion from the mean. As deviations are squared during the calculation process, the result is always positive. Thus, the standard deviation provides a measure of spread that is always non-negative.
5. How does the standard deviation relate to the shape of a frequency distribution?
Ans. The standard deviation is closely related to the shape of a frequency distribution. It helps determine whether the distribution is symmetric or skewed. In a symmetric distribution, the mean, median, and mode are approximately equal, and the standard deviation provides a measure of how close the data values are to this central tendency. In a skewed distribution, where the mean, median, and mode differ, the standard deviation can help identify the extent of the skewness. A higher standard deviation in a skewed distribution indicates a wider spread on one side of the distribution.
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