The relationship between the mean and the median depends on the shape of the distribution. In a symmetric distribution, the mean and median are equal, so if the mean is 105, the median would also be 105. However, if the distribution is skewed, the median could be less than or greater than the mean. Without additional information about the distribution's shape, we cannot definitively determine the median.
The median of the 12 primes less than 40 is 15.
Actually, the median is more resistant to outliers than the mean. The median represents the middle value of a data set when arranged in order, making it less influenced by extreme values. In contrast, the mean is calculated by averaging all values, which can be significantly affected by outliers. Therefore, the median provides a better measure of central tendency when outliers are present.
The median is less effected by outliers or numbers far outside of the normal range than the mean. See related link.
The mean is better than the median when there are outliers.
One of the characteristics of mean when measuring central tendency is that when there are positively skewed distributions, the mean is always greater than the median. Another characteristic is that when there are negatively skewed distributions, the mean is always less than the median.
If the distribution is not symmetric, the mean will be different from the median. A negatively skewed distribution will have a mean hat is smaller than the median, provided it is unimodal.
IDN
When the data distribution is negatively skewed.
The relationship between the mean and the median depends on the shape of the distribution. In a symmetric distribution, the mean and median are equal, so if the mean is 105, the median would also be 105. However, if the distribution is skewed, the median could be less than or greater than the mean. Without additional information about the distribution's shape, we cannot definitively determine the median.
definantly, yes Of course. 1, 2, 3, 40, 50, 60, 82 Mean = 34 Median = 40
The question is how do the mean and median affect the distribution shape. In a normal curve, the mean and median are both in the same point. ( as is the mode) If a distribution is skewed, its tail is either on the right or the left. If a distribution is skewed the median may be a better value to use than the mean since it has less effect on the shape. Also is there are large outliers, the median has less effect and is better to use. So the mean has a bigger effect on the shape many times than the median.
If the distribution is positively skewed , then the mean will always be the highest estimate of central tendency and the mode will always be the lowest estimate of central tendency (If it is a uni-modal distribution). If the distribution is negatively skewed then mean will always be the lowest estimate of central tendency and the mode will be the highest estimate of central tendency. In both positive and negative skewed distribution the median will always be between the mean and the mode. If a distribution is less symmetrical and more skewed, you are better of using the median over the mean.
In a negatively skewed distribution, the mean is typically less than the median, and the median is less than the mode. This results in a tail that extends longer to the left. Therefore, any statement claiming that the mean is greater than the median or that the mode is less than the median would be false. Thus, one must be careful to identify which statements accurately reflect the characteristics of negatively skewed distributions.
median
The median of the 12 primes less than 40 is 15.
(1, 5, 97, 99, 100, 100) The mode is 100. The median is 98. The mean is 67.