The Average Person Does Not Exist – Why the Mean Can Be Misleading

By- Dr. Pavithra .M R

Assistant Professor, Easwari School of Liberal Arts, SRM University – AP

We live in a world obsessed with averages. The average salary, average household income, average spending, average marks, average age, average life expectancy we see these numbers everywhere. They appear in newspapers, government reports, company presentations, advertisements and social media posts. There is something reassuring about an average because it takes a complicated reality and reduces it to one simple number. But there is a catch. The average may describe a group quite accurately while describing almost nobody in that group. The “average person” we keep talking about may exist mathematically but rarely exists in real life.

The Comfort of One Number

Statistics gives us a remarkably simple way of summarising information. Add all the values, divide by the number of observations and we have the mean. The calculation is easy. Understanding what that number actually means is much harder. Imagine five people earning ₹20,000, ₹25,000, ₹30,000, ₹35,000 and ₹40,000 a month. Their average income is ₹30,000 and that number gives us a reasonable picture of the group. Now change just one person’s income to ₹2 lakh. Suddenly, the average jumps significantly. Mathematically, nothing is wrong. But if we tell someone that the “average income” of the group is around ₹59,000, they may imagine that most people earn somewhere near that amount. They don’t, one person’s income has pulled the average upwards. That is the fascinating and sometimes dangerous thing about the mean. It can be perfectly correct and still give us the wrong impression.

When Salary Numbers Create an Illusion

Consider a company announcing that its employees earn an average salary of ₹12 lakh a year. It sounds impressive. A young graduate looking at the company’s recruitment advertisement might assume that ₹12 lakh is what a typical employee earns. But suppose most employees earn between ₹5 lakh and ₹8 lakh, while a handful of senior executives earn several lakhs. The average could rise substantially because of those few very high salaries. The company has not necessarily lied. The calculation may be completely accurate but the number does not tell the whole story. This is where the median becomes important. If all the salaries are arranged from the lowest to the highest, the median is the middle value. Unlike the mean, it is much less affected by extremely high or extremely low salaries. If most employees earn around ₹6–8 lakh and only a few earn crores, the median may provide a much better picture of what a typical employee actually earns. This distinction is not merely a statistical technicality. It can change how we understand inequality, career opportunities and living standards.

The Household That Doesn’t Exist

Household spending provides another good example. We frequently hear that the average household spends a certain amount each month on food, education, transport or healthcare. Such figures can be useful for understanding broad economic trends but the “average household” can be an imaginary creature. Think about the differences between a young professional living alone, a family with two school-going children, a retired couple and a large joint family. Their expenses, priorities and financial pressures can be completely different. Yet all of them may be included in the same calculation. The resulting average may be statistically useful but it does not necessarily describe any one of those families. This matters when governments formulate policies, companies design products or families compare their own spending with national or regional statistics. If we assume that the average household represents everyone, we may end up designing solutions for a household that exists only on paper.

The Student Who Is Below Average

Education provides perhaps the most familiar example. Teachers often talk about the average score of a class. Suppose the average mark in an examination is 70. It sounds as though most students probably scored somewhere around 70. But imagine that half the class scored between 40 and 55, while the other half scored between 85 and 95. The average could still be around 70. There may not even be a student who scored exactly around the average. This is why a teacher looking only at the average class score can miss the real story. There may be a group of students who need considerable support and another group that needs greater academic challenge. The same average can hide two completely different educational realities. Averages are useful summaries. They are not substitutes for understanding individuals.

The Business Dashboard Looks Good

Businesses have their own version of the same problem. Managers regularly look at average sales, average transaction value, average customer spending, average productivity and average response time. These numbers are useful but they can also create a false sense of comfort. Imagine two sales teams that each generate an average of ₹10 lakh a month. At first glance, they appear identical. But suppose every salesperson in Team A consistently generates close to ₹10 lakh, while Team B has two exceptional performers generating most of the revenue and several employees contributing very little. The average is the same but the management challenge is completely different. Team A may have a healthy and consistent system. Team B may have a serious dependency problem. The average has not lied. We simply asked it to answer a question it was never designed to answer. This is why a good analyst looks beyond the mean. We need to understand the spread of the data, the unusual observations, the distribution and the reasons behind the differences.

We Also Compare Ourselves With Averages

The problem becomes more personal when we start using averages to judge ourselves. We compare our salary with the average salary. Parents compare their children’s marks with the class average. Businesses compare their growth with industry averages. People compare their spending, savings and lifestyles with what they believe is “normal.” But being below average does not automatically mean being unsuccessful. A person’s income may be below the national average but perfectly appropriate for their circumstances. A student’s marks may be below the class average while their understanding has improved enormously. A small business may have lower revenue than its competitors but stronger profitability and better long-term prospects. Numbers provide information. They do not provide judgement. The moment we use an average as a benchmark for human worth, we have moved beyond statistics and into comparison and comparison can be deeply misleading.

The Mean Is Not the Villain

It would be wrong to conclude that the mean is a bad measure. It is one of the most useful tools in statistics. Researchers, economists, businesses, governments and scientists use averages every day to understand patterns and make decisions. Without them, analysing large amounts of information would be far more difficult. The problem is not the average itself. The problem is treating the average as the complete story. Whenever we see an average, we should become curious. What does the distribution look like? Are there unusually high or low values? Is the data heavily skewed? Would the median tell us something different? How much variation exists among the observations? These are simple questions but they can completely change our interpretation.

Look Beyond the Average

We are living in an age in which numbers influence almost every important decision. We see statistics in news reports, advertisements, financial statements, election discussions, health claims, educational rankings and business dashboards. Being statistically literate therefore means more than knowing how to calculate a mean. It means knowing when a number deserves our confidence and when it deserves another question. The next time you hear that the average salary is ₹X, the average family spends ₹Y or the average student scores Z, don’t immediately accept the number as a picture of reality. Ask what is happening behind it. Because behind every average are people who are different from one another. Some are doing exceptionally well. Some are struggling. Some are just beginning. Some are far above the number, while others are far below it.

The average can describe the crowd but it cannot define the individual.

Perhaps that is the most important lesson statistics can teach us. Numbers help us see patterns but wisdom comes from understanding what those numbers leave out. In a world increasingly driven by data, we should not become people who merely know the numbers. We should become people who know how to question them. After all, the most important story in a dataset is sometimes the one hidden behind its average.