It is simple to calculate.
Put all the numbers in order and the median is the number that is in the middle!
One disadvantage of using the median is that it may not accurately represent the entire dataset if there are extreme outliers present, as the median is not influenced by the magnitude of these outliers. Additionally, the median may not be as intuitive to interpret as the mean for some individuals, as it does not provide a direct measure of the total value of the dataset. Finally, calculating the median can be more computationally intensive compared to other measures of central tendency, especially with large datasets.
You can find it by using the Pythagorean theorem if you know the side and the base of triangle. In an isosceles triangle the median is also the altitude. The formula is: (The measure of the side length)^2 - (The measure of the one half of the base length )^2 = (The measure of the altitude)^2. Find the square root of the result that you'll have the measure of the altitude.
So that you don't have as many different answers to work with
The variance or standard deviation.
Central tendency is measured by using the mean, median and mode of a set of numbers. Variation is measured by using the range, variance and standard deviation of a set of numbers.
It is simple to calculate.
to know what is the measure
The median or mode should be used instead of the mean in distributions with extreme outliers. In such cases, the mean can be a misleading measure of central tendency and the median value or the mode value are typically more accurate measures.
The median can be calculated using the Median function. Assuming the values you wanted the median of were in cells B2 to B20, you could use the function like this: =MEDIAN(B2:B20)
Not normally because meters would be more appropriate
Put all the numbers in order and the median is the number that is in the middle!
Salad dressing is commonly measured using a tablespoon-size measuring spoon.
You cannot because the standard deviation is not related to the median.
One disadvantage of using the median is that it may not accurately represent the entire dataset if there are extreme outliers present, as the median is not influenced by the magnitude of these outliers. Additionally, the median may not be as intuitive to interpret as the mean for some individuals, as it does not provide a direct measure of the total value of the dataset. Finally, calculating the median can be more computationally intensive compared to other measures of central tendency, especially with large datasets.
A weighted mean is probably best. Certainly better than a median which throws away information from most of the observations.