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Example of Mean Deviation about Median for Continuous Frequency Distribution Video Lecture | Mathematics for GRE Paper II

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FAQs on Example of Mean Deviation about Median for Continuous Frequency Distribution Video Lecture - Mathematics for GRE Paper II

1. What is the formula for calculating mean deviation about median for a continuous frequency distribution?
Ans. The formula for calculating mean deviation about median for a continuous frequency distribution is: Mean Deviation about Median = ∑(|X - M| * f) / N Where: X represents the midpoint of each class interval, M represents the median of the distribution, f represents the frequency of each class interval, N represents the total number of observations.
2. How is the median calculated for a continuous frequency distribution?
Ans. To calculate the median for a continuous frequency distribution, follow these steps: 1. Arrange the data in ascending order. 2. Calculate the cumulative frequencies. 3. Find the median class, which is the class interval that contains the median. 4. Use the formula: Median = L + ((N/2 - F) / f) * w - L represents the lower limit of the median class, - N represents the total number of observations, - F represents the cumulative frequency of the class before the median class, - f represents the frequency of the median class, - w represents the width of the class interval.
3. What does mean deviation about median tell us about a continuous frequency distribution?
Ans. Mean deviation about median is a measure of dispersion that tells us how far, on average, the data points are from the median in a continuous frequency distribution. It provides an indication of the spread or variability of the data around the median. A smaller mean deviation about median indicates that the data points are closer to the median, while a larger mean deviation about median suggests a greater dispersion.
4. How does mean deviation about median differ from mean deviation about mean?
Ans. Mean deviation about median and mean deviation about mean are both measures of dispersion, but they differ in terms of the central tendency they are based on. Mean deviation about median uses the median as the measure of central tendency, while mean deviation about mean uses the mean. The choice of central tendency affects the interpretation of the dispersion measure. Mean deviation about median is less affected by extreme values or outliers compared to mean deviation about mean, making it a more robust measure in certain situations.
5. Can mean deviation about median be negative?
Ans. No, mean deviation about median cannot be negative. The absolute values of the differences between each data point and the median are summed up in the formula for mean deviation about median. Therefore, the resulting value will always be non-negative. In other words, the mean deviation about median measures the average distance of the data points from the median without considering their direction, resulting in a positive value.
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