by getting the mean and multiply by 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.
A weighted mean is probably best. Certainly better than a median which throws away information from most of the observations.
It depends on the particular set of numbers. Which is closest to the majority of the numbers.If all are random or completely Different numbers maybe the median?If they are really different, median is the best.If they are close to the same, the mode is better.There is no measurement better than the other, unless the data contains outliers.Mean is the most common, but if the data set contains outliers then consider using median or mode.In ADDITON:Which is better between mean, median and mode also depends on which type of data are we considering. There are basically 3 kinds of data:Nominal Data (qualitative data). For eg, marital status can be married, single, divorced or de facto.Ordinal data = the data are actually ranked, for eg Google is the number 1 search engine and yahoo is the no 2 search engine.Interval (numerical): for example: age, height, length, breadth etc.If we are looking at an interval(numerical) data, we can use any mean, median or mode. Mean is generally the best measure for statistical interference if there are no extreme values. When there are extreme values it is better to use median. Mode is very rarely used.If we are looking at nominal data, we cannot calculate mean. Like in the given example, marital status can be married, single, divorced or de facto. Now look at the following tableStatus FrequencyMarried 40Single 60Divorced 20De facto 10In this case we have to choose mode. The same is applicable for shoe size, waist size etc.If we are looking for an ordinal data, where data are ranked, the best measure of central tendency will be median.Apart from the type of data, nature of investigation in hand also affects which measure should be choose. In such cases, a personal judgment should be applied. An example is, if we are tying to compare how good a class did, in comparison with other classes, the best measure of central tendency would be mean. however, if we are looking inside a class and trying to compare how well we did in our class, median would be the best measure of central tendency. Unless the data is nominal, it is very rare that mode is the best measure of central tendency.
It is one measure - not the only one - of a "central tendency". It is the same as the "average". To calculate the average, just add all the numbers, and divide the result by the amount of numbers.
Median
Mean, Median, and Mode
The popular two ones are the mean and median. Often mode is included in the list even though it is not a measure of central tendency.
It is the mean.
they measure the same
The three commonly used measures of central tendency are the mean, the median, and the mode. They are different ways of describing a "typical" member of the population.
The central tendency can be summarised by the mode, median or mean. For qualitative data, only the mode is available.The central tendency can be summarised by the mode, median or mean. For qualitative data, only the mode is available.The central tendency can be summarised by the mode, median or mean. For qualitative data, only the mode is available.The central tendency can be summarised by the mode, median or mean. For qualitative data, only the mode is available.
by getting the mean and multiply by the median
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 appropriate measure of central tendency for age is the median. This is because age is a continuous variable and can have outliers or extreme values, which can skew the mean. The median provides a more robust estimate of the center of the distribution.
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.
The mean is the measure of central tendency that is most affected by a few large or small numbers. The median is more robust for extreme values.