If you are studying statistics, it is essential to have a grasp on measures of central tendency before delving into standard deviation. For those familiar with mean, let's continue!
Standard deviation is a measure of how much the values in a data set vary from the mean. It is useful in determining the spread of data points from the average.
The standard deviation formula is:
σ = √(∑(x-μ)^2/N)
Where:
In simpler terms, standard deviation is calculated by finding the square root of the sum of the squared difference between each data point and the mean, divided by the total number of data points.
Standard deviation is a valuable tool for predicting the probability of data points falling within a certain distance from the mean. It assumes that the data points follow a normal distribution, with values evenly spread around the mean in a bell-shaped curve.
The visual representation of a normal distribution can be seen in the graph below:
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