How can you explain the concept of standard deviation to a non-expert?

Before delving into standard deviation, it's important to understand the mean, or average. The mean is calculated by summing all values and dividing by the number of values. For example, to find the average age in a room, you would add all the ages together and divide by the number of people. Standard deviation builds on this concept by measuring how much individual values differ from the mean. It helps determine if the ages are similar or if they vary widely. In statistics, standard deviation is crucial for understanding the spread of data around the mean.

Standard deviation measures how spread out numbers are in a set. Imagine a group of students test scores: if everyone scores around the same, the standard deviation is low, showing little variation. If scores vary widely, the standard deviation is high. It’s like an average distance from the average score. A low value means scores are close to the mean, while a high value means they're more spread out.

Standard deviation is a measure of how spread out the numbers in a set are. Imagine you and your friends are playing a game where you each guess the number of candies in a jar. If most of your guesses are close to the actual number, the standard deviation is small, meaning everyone’s guesses are similar. If the guesses are very different from each other, the standard deviation is large, showing a wide range of guesses. In simple terms, it tells us whether the numbers in a group are close to each other or spread out.

Se você escutar alguém falar sobre "desvio padrão" de uma pesquisa, não se assuste. Trata-se de um indicador de quanto os resultados estão "espalhados" em relação à sua média. Um exemplo prático: Você mede o peso dos alunos de uma sala de aula e descobre que a média desses pesos é de 60 quilos. Digamos que o desvio padrão, calculado com uma fórmula estatística, seja de 3 quilos. Isso significa que a maioria dos alunos (aproximadamente 2/3) terá seu peso entre 57 e 63 quilos.

It is important to read and learn the concept of any statistical tool before applying and where to apply, the standard deviation as it is represented by SD is a measure that is used to quantify the amount of variation or dispersion of a set of data values. A low standard deviation indicates that the data points tend to be close to the mean of the set, while a high standard deviation indicates that the data points are spread out over a wider range of values.

If you have a set of values, first you need to calculate the mean of all observations and divide it by the total number of observations, then substract each value from the mean and square it. Determine the average of all of those squared numbers calculated in second step to obtain what we called the variance. Finally the square root of the numbers obtained in last step is the standard deviation.

Imagine you and your friends are all different heights. The average height is like the middle line on a seesaw. Standard deviation is how far each of you is from that middle line. If everyone is close to the middle, the standard deviation is small. If some are really tall or really short, the standard deviation is big. It helps us understand how spread out things are.