# Kotlin Program to Calculate Standard Deviation

#### In this program, you’ll learn to calculate the standard deviation using a function in Kotlin.

This program calculates the standard deviation of a individual series using arrays. Visit this page to learn about Standard Deviation.

To calculate the standard deviation, `calculateSD()`

function is created. The array containing 10 elements is passed to the function and this function calculates the standard deviation and returns it to the `main()`

function.

## Example: Program to Calculate Standard Deviation

```
fun main(args: Array<String>) {
val numArray = doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0)
val SD = calculateSD(numArray)
System.out.format("Standard Deviation = %.6f", SD)
}
fun calculateSD(numArray: DoubleArray): Double {
var sum = 0.0
var standardDeviation = 0.0
for (num in numArray) {
sum += num
}
val mean = sum / 10
for (num in numArray) {
standardDeviation += Math.pow(num - mean, 2.0)
}
return Math.sqrt(standardDeviation / 10)
}
```

When you run the program, the output will be:

Standard Deviation = 2.872281

In the above program, we’ve used the help of *Math.pow()* and *Math.sqrt()* to calculate the power and square root respectively.

# Python Example for Beginners

## Two Machine Learning Fields

There are two sides to machine learning:

**Practical Machine Learning:**This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.**Theoretical Machine Learning**: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.

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