How to Interpret a Standard Deviation of Zero?
How to Interpret a Standard Deviation of Zero?, The standard deviation is a statistic that measures the spread of values in a sample.
The standard deviation of a sample can be calculated using the formula below:
sd=√Σ(xi – xbar)2/(n-1)
Σ: A symbol that means “sum”
xi: The ith value in the sample
xbar: The mean of the sample
n: The sample size
The higher the standard deviation, the more evenly distributed the data in a sample are.
The lower the standard deviation, the more closely the data are packed together.
When a sample’s standard deviation is 0, it signifies that every value in the sample is the same.
In other words, the values have zero spread.
In reality, the following example demonstrates how to understand a standard deviation of zero.
How to Interpret a Standard Deviation of Zero
Let’s say we take an example of ten panelist ratings for a particular product
The mean of product likeability is 9.
We can compute the sample standard deviation (s) for this dataset using this information.
sd = √Σ(xi – xbar)2 / (n-1)
sd = √((9 – 9)2 + (9 – 9)2 + (9 – 9)2 + … + (9 – 9)2/ (10-1)
sd = 0
The sample standard deviation turns out to be 0.
The distribution of values in the dataset is exactly zero because every panelist has the same ratings.
Will Standard Deviation in the Real World Ever Be Zero?
It’s feasible that a real-world dataset has zero standard deviation, but this is uncommon.
When gathering small samples for infrequent events, the most likely possibility is to encounter a standard deviation of zero.
Consider gathering statistics on the number of traffic accidents in a certain municipality over a one-week period.
It’s probable that you’ll acquire the following information.
data<-c(0,0,0,0,0,0,0) mean(data)  0 sd(data)  0
The mean number of daily accidents and the standard deviation would both be zero in this situation.
Alternatively, suppose you collect the following information on the number of monthly sales of a highly-priced product for a corporation during a 6-month period.
Because the product is so pricey, the company only sells five each month.
The mean number of monthly products sold in this situation is five, and the standard deviation of monthly product sales is zero.
When you see a standard deviation of zero in a real-world dataset, it simply signifies that every value in the dataset is the same.