For some kinds of distributions one, for others kinds, the other.
The median is more useful than the mean in situations where the data set contains outliers or is skewed. For example, in household income data, where a few extremely high incomes can distort the average, the median provides a better representation of the typical income level. This makes the median a more reliable measure for understanding central tendency in such cases.
The median is 5, because two values (2 and 2) are less than 5, and an equal number of values (8 and 9) are greater than 5. Generally speaking, the median is more informative than the average (mean), although a proper calculation of a "typical value" of a list of values depends on what the typical value will be used for.
Data sets illustrate that the median is more resistant to outliers and extreme values than the mean. While the mean can be significantly affected by extreme data points, causing it to misrepresent the central tendency, the median remains stable as it focuses solely on the middle value of a sorted data set. This property makes the median a better measure of central tendency in skewed distributions. Thus, when analyzing data, choosing the median over the mean can provide a clearer picture of the typical value.
The mean is the arithmetic average of a set of values, while the median is the middle value when the data is ordered. In symmetrical distributions, the mean and median are typically close or equal, but in skewed distributions, the mean can be influenced by extreme values, making it higher or lower than the median. Thus, the median is often preferred as a measure of center for skewed data, as it provides a better representation of the typical value without being affected by outliers.
In maths, the median is connected with the mode, mean. Help learn theese by singing a song, more of a chant though. Mode most Median middle Mean add up and divide Mode most Median middle Mean add up and divide!!
Average. this is because the typical is what the total divided by the number of items. this is also what the mean (or average) is.
In the appropriate context, they do.
The median is more useful than the mean in situations where the data set contains outliers or is skewed. For example, in household income data, where a few extremely high incomes can distort the average, the median provides a better representation of the typical income level. This makes the median a more reliable measure for understanding central tendency in such cases.
When the distribution has outliers. They will skew the mean but will not affect the median.
Either can be used for symmetrical distributions. For skewed data, the median may be more a appropriate measure of the central tendency - the "average".
Mean.
Both the mean and median represent the center of a distribution. Calculating the mean is easier, but may be more affected by outliers or extreme values. The median is more robust.
The median is 5, because two values (2 and 2) are less than 5, and an equal number of values (8 and 9) are greater than 5. Generally speaking, the median is more informative than the average (mean), although a proper calculation of a "typical value" of a list of values depends on what the typical value will be used for.
in general,mean is more stable than median but in the case of extreme values it is better to consider median a stable measure than mean.
The mean is the arithmetic average of a set of values, while the median is the middle value when the data is ordered. In symmetrical distributions, the mean and median are typically close or equal, but in skewed distributions, the mean can be influenced by extreme values, making it higher or lower than the median. Thus, the median is often preferred as a measure of center for skewed data, as it provides a better representation of the typical value without being affected by outliers.
The mean deviation from the median is equal to the mean minus the median.
Median age gives a more accurate representation of the central tendency of a population's age distribution, as it is less affected by outliers compared to the mean. It provides a clearer understanding of the typical age of a population and can be useful for demographic analysis and policy making.