Difference Between Mean vs Median
A mean is the simple arithmetic average, or one can say it is the mathematical average of a set of 2 or more numerical. The mean for any given set of numerical can be computed in more than a single way, which will include the arithmetic mean method, which uses the summation of the numerical in the series, and the other method is the geometric mean method. Median is the middlemost numerical in a sorted list of those numerical. To determine the median value in a sequence of numerical, the numerical must be first arranged in value order which is from lowest to highest, or in other words, in ascending order. If there is an odd amount of numerical, the median value is numerical, which is in the middle, with the same amount of numerical above and below. If there is an even amount of numerical in the list, then the middle pair must be first determined, then they are added together, and then they are divided by two to find the median value. It can be used to determine an approximate mean or average. The median is, however, sometimes used as opposed to the average or the mean when the data sets have outliers in the sequence that can lead to the skewness of the average of the values. The median of a sequence can actually be less affected by those outliers when compared with the average or the mean.
Head To Head Comparison Between Mean vs Median (Infographics)
Below is the top 6 difference between Mean vs Median:
Key differences between Mean vs Median
Both Mean vs Median are popular choices in the market; let us discuss some of the major differences
- In statistics, a mean can be defined as the simple average or simple arithmetic average of the given set of data or quantities or values. The median, on the other hand, is said to be the middlemost numerical in an ordered list (whether ascending or descending) of values.
- While the mean, as stated earlier, is the arithmetic average, and on the other hand, the median is the positional average, the position of the data set will help in determining the value of the median.
- Mean outlines the center of the gravity of the data set or the sample, whereas the median will highlight the middle-most value of the sample or the data set.
- The mean, as mentioned earlier, will be appropriate for normally distributed data. On another end, the median is more suitable and is the best option when the data set or the sample or the distribution is skewed.
- The mean is highly and is extremely affected by the outliner or the extreme value, and the same is not in the case with a median.
- The mean or the average can be calculated by summing up or adding up all the observations in the given data set and then dividing the value that is obtained with the number of the observations in the sample; the results will be the mean. As opposed to that, the median, the data set, or the sample given will be arranged in an ascending or descending order, and then the value which falls in the exact middle or the center of the new data set or the sample will be the median.
Mean vs Median Comparison Table
Below is the topmost comparison between Mean vs Median
| The Basis Of comparison |
Mean |
Median |
| Basic Definition | It can be referred to as the simple average or athematic average of the given set of data or the quantities or the values. | It can be defined as the middlemost numerical in an ordered list (i.e. from lowest to highest or vice versa) of values. |
| Meaning | It n can also be termed as arithmetic average. | It can be meant as a positional average. |
| Type of distribution | For Mean, a normal distribution would apply. | For the median to be used and to find it as more appropriate to use than the mean, there should be skewed distribution. |
| Calculation | It can be calculated by adding up or taking up the sum of all the observations or the data set and then dividing that summation of the value obtained by the number of observations in the sample provided. | To calculate it, the first one needs to be arranged the data set in ascending or in descending order, and then the value which shall fall in the exact middle of the new data set or of the sample will be the median. |
| What does it represent? | It will represent the central gravity of the data set given. | The mid-point of the data set will be represented by it. |
| Outliners bias | It is largely affected by the outlines, and hence it’s not the appropriate method to be used to find the average. | It is unaffected by the outliners. |
Conclusion
After discussing the above points, one can conclude that both Mean vs Median is mathematical concepts and are not one and the same but are different. Mean or the arithmetic mean can be considered as one of the best measures of central tendency due to its features which are of an ideal measure, but it also has a drawback that the sampling fluctuations will influence the average.
In a similar way, the median is also not ambiguously defined and is easy to calculate and understand, and the good thing about this measure is that the same is not affected by the sampling fluctuations, but the only limitation of the median is that the same is not based on all observations. For open-ended classification, the median will be normally preferred over the mean. A central tendency implies the tendency of the data points or the data sets to cluster around its middle-most or central value. The most recognized types of these descriptive statistics are the median, mean, and mode, which are used at almost all of the levels of statistics and math, whether it be academics or sports or investing or studying a country’s economics.
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