Introduction

In statistics, the median separates a data sample’s higher half from the lower half. For a data set, it may be thought of as the “middle” value. Though other estimators have been proposed, the median remains one of the most popular because it is easy to understand and computationally straightforward. The median estimate from a sample is also called an estimate of the population median.

Theoretical Background

Z-scores are a very useful statistical tool. A z-score tells you how many standard deviations a data point is from the mean. Z-scores are also known as standardized scores. A z-score can be calculated from raw data by subtracting the mean and then dividing by the standard deviation.

Definitions

In mathematics, a z-score is the number of standard deviations a data point is from the mean.

For example, if the mean score on a test is 70 and the standard deviation is 10, then a score of 80 would have a z-score of 1. A score of 60 would have a z-score of -1.

The median is the value that lies at the midpoint of a dataset. Half of the values will be above this point and half will be below it.

To find the median, you first need to put all of the values in order from smallest to largest (or vice versa). Then, if there is an odd number of values, the median will be the value in the middle. If there is an even number of values, you take the two middle values and find their mean.

The Z-Score

The Z-score is a statistical measure that tells you how far away a specific data point is from the mean of the data set. In other words, it measures how many standard deviations away from the mean a data point is.

The formula for calculating a Z-score is:

Z = (X – μ) / σ

X = the value of the data point
μ = the mean of the data set
σ = the standard deviation of the data set

So, if X is equal to the median of the data set, then the corresponding Z-score would be:
Z = (median – μ) / σ

The Relationship Between the Z-Score and the Median

The z-score corresponding to the median for any distribution is always 0. This is because the median is the value that is exactly in the middle of the distribution. The z-score is simply a measure of how many standard deviations away from the mean the median is.

Proof

Let’s assume that we have a distribution with a median of zero. That is, 50% of the values are negative and 50% are positive. The z-score corresponding to the median would be zero. That is, if you took a random sample from this distribution, the z-score would be zero half of the time.

Conclusion

There is no definitive answer to this question as it depends on the distribution in question. However, in general, the z-score corresponding to the median can be found by calculating the difference between the median and the mean, and dividing by the standard deviation.