When the mean and median are equal, what can be said about the shape of the distribution? a.More information should be presented if assumptions pertaining to the shape of the distribution are to be made b.When the mean is equal to the median, the shape of the distribution tends to be slightly skewed right c.When the mean is equal to the median, the shape of the distribution can be assumed relatively symmetrical d.When the mean is equal to the median, the shape of the distribution tends to be slightly skewed left

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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When the mean and median are equal, what can be said about the shape of the distribution?

	a.	More information should be presented if assumptions pertaining to the shape of the distribution are to be made
	b.	When the mean is equal to the median, the shape of the distribution tends to be slightly skewed right
	c.	When the mean is equal to the median, the shape of the distribution can be assumed relatively symmetrical
	d.	When the mean is equal to the median, the shape of the distribution tends to be slightly skewed left

Definition Definition Middle value of a data set. The median divides a data set into two halves, and it also called the 50th percentile. The median is much less affected by outliers and skewed data than the mean. If the number of elements in a dataset is odd, then the middlemost element of the data arranged in ascending or descending order is the median. If the number of elements in the dataset is even, the average of the two central elements of the arranged data is the median of the set. For example, if a dataset has five items—12, 13, 21, 27, 31—the median is the third item in ascending order, or 21. If a dataset has six items—12, 13, 21, 27, 31, 33—the median is the average of the third (21) and fourth (27) items. It is calculated as follows: (21 + 27) / 2 = 24.

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