Normal

What is it?

As an emergency room physician, I often get asked, “Is that normal?” But the problem is that “normal” doesn’t truly apply to an individual. ” Normal” applies to populations. It is a statistical tool. The root word is “norm.” And here is what that means. (this is a pun, as “mean” also is a term used to represent “norm.” But I digress.)

Quick example: I diagnose a patient with gallstones. The patient might ask in a rebuttal, “Why was I not having nausea and vomiting? Is that normal?” So the answer to that is, “Having gallstones is not normal.” So, anything that comes or does not come with the gallstones is “normal” for you. And you, only. So “normal” does not even really apply. It’s common to think of a disease as being diagnosed by the complex of symptoms. In the case of gallstones, they are diagnosed by ultrasound. If I see gallstones on ultrasound, you have gallstones. What symptoms you have to do not have would not apply.

In statistics, the “norm” refers to the typical or average value of a set of data. It represents what is considered standard or usual in a particular context. To derive the norm, we add all the values in the data set and divide the sum by the number of data points.

An Example

Let’s say we want to find the norm (average) of exam scores: 85, 90, 78, 92, and 88. First, we add them together: 85 + 90 + 78 + 92 + 88 = 433. Next, we divide this sum by the number of scores, which is 5 (since we have five scores). So, 433 ÷ 5 = 86.6.

The norm, in this case, is 86.6, which is the average of the exam scores. It represents the typical performance of the students in the group. The norm helps us understand the overall performance, and we can use it as a reference point to compare individual scores.

This is a Normal Distribution or Bell Curve.

Deviations from “normal”

However, the norm might not always reflect everyone’s experience accurately. For example, suppose one student scored much lower or higher than the rest. In that case, the average might not best represent their performance. In such cases, additional statistics like the median (middle value) or standard deviation (how much scores vary) can provide a more comprehensive picture.

In the graph above, the arrow represents the “mean.” The lines lateral to that represent “standard deviations” from the mean. One “standard deviation” represents 68% of all scores. Going out to two standard deviations, you cover 95% of all scores. Three equals 99.7%, and so on. “Sigma” is a symbol for standard deviation, and some of you in business and manufacturing are used to the term “Six Sigma.” That means you are trying to get less than one error in a million. Six standard deviations is roughly 1 in a million.

The norm is widely used in various fields, from education and business to healthcare and social sciences. It allows us to make informed decisions, identify outliers, and assess how data compares to expectations. Understanding the norm helps us gain valuable insights from data and make meaningful interpretations that influence decision-making.

“Normal,” In Conclusion

“Normal” generally means something typical, usual, or expected in a given context or situation. It serves as a standard or baseline against which other things are compared. Normal can vary depending on age, health, and social norms. It helps identify deviations from what is considered standard or healthy. While “normal” often implies something positive or acceptable, it is essential to remember that normality is subjective and can change over time and across cultures. Embracing diversity and understanding individual differences is crucial, as what might be expected of one person could differ from another. Avoiding judgments based on perceived normality promotes inclusivity and compassion toward others. Sometimes, aspiring to meet societal norms might cause unnecessary pressure or stress. Accepting individuality and respecting diverse perspectives can lead to a more understanding and inclusive society.

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