In a normal distribution, data is symmetrically distributed with no skew. When plotted on a graph, the data follows a bell shape, with most values clustering around a central region and tapering off as they go further away from the center.
Normal distributions are also called Gaussian distributions or bell curves because of their shape.
Why do normal distributions matter?
All kinds of variables in natural and social sciences are normally or approximately normally distributed. Height, birth weight, reading ability, job satisfaction, or SAT scores are just a few examples of such variables.
Because normally distributed variables are so common, many statistical tests are designed for normally distributed populations.
Understanding the properties of normal distributions means you can use inferential statistics to compare different groups and make estimates about populations using samples.
Real-Life Examples Of Normal Distribution
1. Birthweight of Babies
It’s well-documented that the birth weight of newborn babies is normally distributed with a mean of about 7.5 pounds.
2. Height of Males
The distribution of height of males in the U.S. is roughly normally distributed with a mean of 70 inches and a standard deviation of 3 inches.
3. Shoe Sizes
The distribution of shoe sizes for males in the U.S. is roughly normally distributed with a mean of size 10 and a standard deviation of 1.
4. ACT Scores
The distribution of ACT scores for high school students in the U.S. is normally distributed with a mean of 21 and a standard deviation of about 5.
5. Average NFL Player Retirement Age
The distribution of retirement age for NFL players is normally distributed with a mean of 33 years old and a standard deviation of about 2 years.
6. Blood Pressure
The distribution of diastolic blood pressure for men is normally distributed with a mean of about 80 and a standard deviation of 20.
7. Height
The height of people is an example of normal distribution. Most of the people in a specific population are of average height.
The number of people taller and shorter than the average height people is almost equal, and a very small number of people are either extremely tall or extremely short.
Several genetic and environmental factors influence height. Therefore, it follows the normal distribution.
8. Rolling A Dice
A fair rolling of dice is also a good example of normal distribution. In an experiment, it has been found that when a dice is rolled 100 times, chances to get ‘1’ are 15-18% and if we roll the dice 1000 times, the chances to get ‘1’ are, again, the same, which averages to 16.7% (1/6).
If we roll two dice simultaneously, there are 36 possible combinations. The probability of rolling ‘1’ (with six possible combinations) again averages to around 16.7%, i.e., (6/36). The more the number of dice more elaborate the normal distribution graph.
9. Tossing A Coin
Flipping a coin is one of the oldest methods for settling disputes. We all have flipped a coin before a match or game. The perceived fairness in flipping a coin lies in the fact that it has equal chances to come up with either result.
The chances of getting a head are 1/2, and the same is true for tails. When we add both, it equals one. If we toss coins multiple times, the sum of the probability of getting heads and tails will always remain 1.
10. IQ : intelligence quotient level
In this scenario of increasing competition, most parents, as well as children, want to analyze the intelligence quotient level.
Well, the IQ of a particular population is a normal distribution curve; where the IQ of a majority of the people in the population lies in the normal range whereas the IQ of the rest of the population lives in the deviated range.
11. Technical Stock Market
Most of us have heard about the rise and fall in the prices of shares in the stock market. These changes in the log values of Forex rates, price indices, and stock price return often form a bell-shaped curve.
For stock returns, the standard deviation is often called volatility. If returns are normally distributed, more than 99 percent of the returns are expected to fall within the deviations of the mean value.
Such characteristics of the bell-shaped normal distribution allow analysts and investors to make statistical inferences about the expected return and risk of stocks.
12. Blood Pressure
Blood pressure generally follows a Gaussian distribution (normal) in the general population, and it makes Gaussian mixture models a suitable candidate for modeling blood pressure behavior.
13. Shoe Size
Have you wondered what would have happened if the glass slipper left by Cinderella at the prince’s house fitted another woman’s feet? He would have ended up marrying another woman.
It has been one of the most amusing assumptions we all have ever come across. As per the data collected in the US, female shoe sales by size are normally distributed because the physical makeup of most women is almost the same.
14. Birth Weight
The normal birth weight of a newborn ranges from 2.5 to 3.5 kg. The majority of newborns have normal birthweight whereas only a few percent of newborns have a weight higher or lower than normal. Hence, birth weight also follows the normal distribution curve.
15. Student’s Average Report
Nowadays, schools are advertising their performances on social media and TV. They present the average results of their school and allure parents to get their children enrolled in that school.
School authorities find the average academic performance of all the students, and in most cases, it follows the normal distribution curve. The number of average intelligent students is higher than most other students.