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 table
Status Frequency
Married 40
Single 60
Divorced 20
De facto 10
In 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.
by getting the mean and multiply by the median
A weighted mean is probably best. Certainly better than a median which throws away information from most of the observations.
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.
The mean.
Mode.
"Measures of central tendency are statistical measures." is an accurate statement.
Benefits of Central Tendency
One of the measures of central tendency IS the average, also known as mean. You can't calculate the average from other measures of central tendency.
"What are the benefits of measures of central tendency? Explain with an example
easures of central tendency
The mean of 9 is 9. The median of 9 is 9. The mode of 9 is 9. These are the commonest measures of central tendency.
well...the measures of the central tendency would be 30 minutes
None. Measures of central tendency are not significantly affected by the spread or dispersion of data.
difference
call thi
The mean and median are two measures of central tendency. In introductory statistics many schools include the mode as another example of central tendency but the mode could well be at the end of a distribution.
Common measures of central tendency are the mean, median, mode. Common measures of dispersion are range, interquartile range, variance, standard deviation.