Introduction to MongoDB $stdDevSamp Operator

$stdDevSamp is an aggregation operator in MongoDB used to calculate the sample standard deviation. Sample standard deviation is a statistic used to describe the dispersion of a set of data and is commonly used to measure the stability and reliability of data. Unlike the $stdDevPop operator, which uses population data, the $stdDevSamp operator uses sample data and is therefore more commonly used in practical data analysis.

Syntax

The syntax of the $stdDevSamp operator is as follows:

{ $stdDevSamp: <expression> }

where <expression> is an expression, typically a field reference, that specifies the data source for calculating the sample standard deviation.

Use Cases

The $stdDevSamp operator is typically used in data analysis scenarios that require the calculation of sample standard deviation, such as:

• Analyzing the volatility of a set of data to understand its risk and stability.
• Comparing the stability of multiple sets of data to make decisions.
• Determining whether a set of data meets a certain quality requirement based on its dispersion.

Examples

Here are two examples.

Example 1

Suppose there is a students collection that contains the name and score of each student. We want to calculate the standard deviation of all students’ scores. This can be achieved using the $stdDevSamp operator.

First, insert some sample data:

db.students.insertMany([
  { name: "Alice", score: 90 },
  { name: "Bob", score: 85 },
  { name: "Charlie", score: 95 },
  { name: "David", score: 80 },
  { name: "Emily", score: 92 }
])

Next, calculate the standard deviation of the scores using the $stdDevSamp operator:

db.students.aggregate([
  {
    $group: {
      _id: null,
      stdDev: { $stdDevSamp: "$score" }
    }
  }
])

Running the above aggregation operation will output a document that contains the standard deviation of the score field:

{ "_id" : null, "stdDev" : 5.220153254455275 }

In this example, the $stdDevSamp operator takes the score field as input and calculates the standard deviation of that field. Then, the $group aggregation operator groups the result by _id as null for outputting the standard deviation.

Example 2

Suppose we have a collection of documents that record ratings for different movies, which contains the following fields:

{ "title": "The Shawshank Redemption", "rating": 9.3 }
{ "title": "The Godfather", "rating": 9.2 }
{ "title": "The Godfather: Part II", "rating": 9.0 }
{ "title": "The Dark Knight", "rating": 9.0 }
{ "title": "12 Angry Men", "rating": 8.9 }
{ "title": "Schindler's List", "rating": 8.9 }
{ "title": "The Lord of the Rings: The Return of the King", "rating": 8.9 }
{ "title": "Pulp Fiction", "rating": 8.9 }
{ "title": "The Good, the Bad and the Ugly", "rating": 8.8 }
{ "title": "Fight Club", "rating": 8.8 }

We can use the $stdDevSamp operator to calculate the standard deviation of all movie ratings. The following code snippet is an example:

db.movies.aggregate([
  {
    $group: {
      _id: null,
      stdDev: { $stdDevSamp: "$rating" }
    }
  }
])

This will return the following result:

{ "_id": null, "stdDev": 0.19104043239027364 }

The result indicates that the standard deviation of all movie ratings is approximately 0.19.

Conclusion

The $stdDevSamp operator is a MongoDB aggregation pipeline operator used to calculate the sample standard deviation of a set of numerical data. It can help us understand the variability of a set of data and gain better insights into the characteristics of the data. When working with data, we can choose an appropriate method of calculating standard deviation based on our needs to analyze data and draw more accurate conclusions.