Why do mean and median differ

Robert is a science writer and visiting professor of science at Aston University. He likes maths, West End musicals and hamsters. It is necessary to see this range because outlier values in our data can distort the results and visualizations. The green line shows the median seconds and the blue line shows the mean value If we want to know the average time spent on customer contacts , the mean and the median show us very different information. So, which one should we trust?

We recommend you to choose the median instead of the mean. Below you can read the reasons. On the next chart, you can see the same dataset but visualized in full range , including outliers 0 to seconds.

That is a big range. It is also easy to see the difference between the median seconds and the mean ,29 seconds values, but now we can also clearly understand how far the outlier values lie.

What if we do not involve the outlier? Using a filter we can see values on the third chart from 0 to now. The value of the mean will change decrease , but the median will not until a bigger change occurs. Forgot Password? Free Excel Course. Login details for this Free course will be emailed to you. Article by Madhuri Thakur. Difference Between Mean and Median Mean and Median are two commonly used terms in mathematics, mean is like average of a given numbers and it sums up the numbers and divide them with the count of numbers which gives us the mean while median on other hand returns the middle number from the whole data set and if the data set is even then median adds the two middle numbers and divides it by 2 giving us the median.

What is Mean? Leave a Reply Cancel reply Your email address will not be published. Please select the batch. Cookies help us provide, protect and improve our products and services. By using our website, you agree to our use of cookies Privacy Policy. We assume that is a correct value, but that a device failure leads to the false measurement of The mean of the resulting five values now is instead of , as calculated from the original data, thus showing a considerable effect of the incorrect measurement.

As before, the value is in the centre of the data row, so the median actually is unaltered by the false measurement. An example for such a distribution in the context of an observational study is the time since the onset of a particular disease.

In many cases, the date of diagnosis is close to the time of reporting, i. However, the study group often also includes patients who have been suffering from the disease for many years.

If we calculate the mean of the individual time spans since disease onset, such large values have an enormous impact, making the mean larger than the actual distribution of data would suggest. Therefore, here the median gives a more realistic picture of the data. If they are not too different , use the mean for discussion of the data, because almost everybody is familiar with it.

If both measures are considerably different, this indicates that the data are skewed i. Stuck in the middle — mean vs.