Module 5 · Dispersion, Shape, and Robust Statistics Lesson 41 of 120
Deviation, Absolute Deviation, and Squared Deviation
Explaining inconsistent settlement time.
Transcript
21 sentences · select one to jump thereCheck your understanding
Are squared deviations still measured in hours?
Code lab
Run it yourself
The lesson source in 7 languages. Edit it, run TypeScript and Python right here, and compare with the expected output.
/**
* Fintech Math Bootcamp · Lesson 041 of 120
* Deviation, Absolute Deviation, and Squared Deviation
* Module 05: Dispersion, Shape, and Robust Statistics
*
* Scenario: Explaining inconsistent settlement time
* Rule: deviation = x − center; magnitude = |deviation|; square = deviation²
*
* Try it: Are squared deviations still measured in hours?
*
* Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/dispersion-shape-and-robust-statistics/deviation-absolute-deviation-and-squared-deviation/
* Free course: https://courses.thefintechbuilder.com
* Synthetic teaching example, not financial advice or a production library.
*/
export function lesson041() {
const hours = [1,2,2,4,9], center = 3.6;
const deviations = hours.map(x => x-center);
const result = {deviations,
absolute: deviations.map(Math.abs),
squared: deviations.map(d => d*d)};
return result;
}
export const checkedResult = {"deviations":[-2.6,-1.6,-1.6,0.3999999999999999,5.4],"absolute":[2.6,1.6,1.6,0.3999999999999999,5.4],"squared":[6.760000000000001,2.5600000000000005,2.5600000000000005,0.15999999999999992,29.160000000000004]};
// Run this file directly: npx tsx lessons/05-dispersion-shape-and-robust-statistics/041-deviation-absolute-deviation-and-squared-deviation.ts
if (process.argv[1] && import.meta.url.endsWith(process.argv[1].replace(/\\/g, "/").split("/").pop()!)) {
console.log(JSON.stringify(lesson041(), null, 2));
}
Your output
Press Run to execute the code in your browser.
Expected output
{
"deviations": [
-2.6,
-1.6,
-1.6,
0.3999999999999999,
5.4
],
"absolute": [
2.6,
1.6,
1.6,
0.3999999999999999,
5.4
],
"squared": [
6.760000000000001,
2.5600000000000005,
2.5600000000000005,
0.15999999999999992,
29.160000000000004
]
}# Fintech Math Bootcamp · Lesson 041 of 120
# Deviation, Absolute Deviation, and Squared Deviation
# Module 05: Dispersion, Shape, and Robust Statistics
#
# Scenario: Explaining inconsistent settlement time
# Rule: deviation = x − center; magnitude = |deviation|; square = deviation²
#
# Try it: Are squared deviations still measured in hours?
#
# Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/dispersion-shape-and-robust-statistics/deviation-absolute-deviation-and-squared-deviation/
# Free course: https://courses.thefintechbuilder.com
# Synthetic teaching example, not financial advice or a production library.
import json
def lesson041() -> dict:
hours, center = [1, 2, 2, 4, 9], 3.6
deviations = [x - center for x in hours]
return {
"deviations": deviations,
"absolute": [abs(d) for d in deviations],
"squared": [d * d for d in deviations],
}
if __name__ == "__main__":
print(json.dumps(lesson041(), indent=2))
Your output
Press Run to execute the code in your browser.
Expected output
{
"deviations": [
-2.6,
-1.6,
-1.6,
0.3999999999999999,
5.4
],
"absolute": [
2.6,
1.6,
1.6,
0.3999999999999999,
5.4
],
"squared": [
6.760000000000001,
2.5600000000000005,
2.5600000000000005,
0.15999999999999992,
29.160000000000004
]
}/**
* Fintech Math Bootcamp · Lesson 041 of 120
* Deviation, Absolute Deviation, and Squared Deviation
* Module 05: Dispersion, Shape, and Robust Statistics
*
* Scenario: Explaining inconsistent settlement time
* Rule: deviation = x − center; magnitude = |deviation|; square = deviation²
*
* Try it: Are squared deviations still measured in hours?
*
* Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/dispersion-shape-and-robust-statistics/deviation-absolute-deviation-and-squared-deviation/
* Free course: https://courses.thefintechbuilder.com
* Synthetic teaching example, not financial advice or a production library.
*/
import java.util.ArrayList;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
public class Main {
static Map<String, Object> lesson041() {
double[] hours = {1, 2, 2, 4, 9};
double center = 3.6;
double[] deviations = new double[hours.length];
double[] absolute = new double[hours.length];
double[] squared = new double[hours.length];
for (int i = 0; i < hours.length; i++) {
deviations[i] = hours[i] - center;
absolute[i] = Math.abs(deviations[i]);
squared[i] = deviations[i] * deviations[i];
}
Map<String, Object> result = new LinkedHashMap<String, Object>();
result.put("deviations", deviations);
result.put("absolute", absolute);
result.put("squared", squared);
return result;
}
public static void main(String[] args) {
System.out.println(toJson(lesson041(), ""));
}
// --- Minimal JSON printer: maps keep insertion order, 2-space indent. ---
static String toJson(Object value, String indent) {
if (value == null) return "null";
if (value instanceof String) return "\"" + value + "\"";
if (value instanceof Double) return formatNumber((Double) value);
if (value instanceof Number) return value.toString();
if (value instanceof double[]) {
List<Object> items = new ArrayList<Object>();
for (double v : (double[]) value) items.add(v);
return toJson(items, indent);
}
String inner = indent + " ";
StringBuilder sb = new StringBuilder();
if (value instanceof Map) {
Map<?, ?> map = (Map<?, ?>) value;
if (map.isEmpty()) return "{}";
sb.append("{\n");
int i = 0;
for (Map.Entry<?, ?> entry : map.entrySet()) {
sb.append(inner).append('"').append(entry.getKey()).append("\": ")
.append(toJson(entry.getValue(), inner))
.append(++i < map.size() ? ",\n" : "\n");
}
return sb.append(indent).append('}').toString();
}
List<?> list = (List<?>) value;
if (list.isEmpty()) return "[]";
sb.append("[\n");
for (int i = 0; i < list.size(); i++) {
sb.append(inner).append(toJson(list.get(i), inner))
.append(i + 1 < list.size() ? ",\n" : "\n");
}
return sb.append(indent).append(']').toString();
}
static String formatNumber(double v) {
if (Double.isNaN(v) || Double.isInfinite(v)) return "null";
if (v == Math.rint(v) && Math.abs(v) < 1e15) return Long.toString((long) v);
return Double.toString(v);
}
}
No browser runner for Java yet
Read the code here, then run it in your own toolchain or a ready-made cloud workspace.
Expected output
{
"deviations": [
-2.6,
-1.6,
-1.6,
0.3999999999999999,
5.4
],
"absolute": [
2.6,
1.6,
1.6,
0.3999999999999999,
5.4
],
"squared": [
6.760000000000001,
2.5600000000000005,
2.5600000000000005,
0.15999999999999992,
29.160000000000004
]
}// Fintech Math Bootcamp · Lesson 041 of 120
// Deviation, Absolute Deviation, and Squared Deviation
// Module 05: Dispersion, Shape, and Robust Statistics
//
// Scenario: Explaining inconsistent settlement time
// Rule: deviation = x − center; magnitude = |deviation|; square = deviation²
//
// Try it: Are squared deviations still measured in hours?
//
// Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/dispersion-shape-and-robust-statistics/deviation-absolute-deviation-and-squared-deviation/
// Free course: https://courses.thefintechbuilder.com
// Synthetic teaching example, not financial advice or a production library.
package main
import (
"encoding/json"
"fmt"
"math"
)
// Deviations holds signed, absolute and squared distances from the center.
type Deviations struct {
Deviations []float64 `json:"deviations"`
Absolute []float64 `json:"absolute"`
Squared []float64 `json:"squared"`
}
func lesson041() Deviations {
hours, center := []float64{1, 2, 2, 4, 9}, 3.6
var result Deviations
for _, x := range hours {
d := x - center
result.Deviations = append(result.Deviations, d)
result.Absolute = append(result.Absolute, math.Abs(d))
result.Squared = append(result.Squared, d*d)
}
return result
}
func main() {
out, _ := json.MarshalIndent(lesson041(), "", " ")
fmt.Println(string(out))
}
No browser runner for Go yet
Read the code here, then run it in your own toolchain or a ready-made cloud workspace.
Expected output
{
"deviations": [
-2.6,
-1.6,
-1.6,
0.3999999999999999,
5.4
],
"absolute": [
2.6,
1.6,
1.6,
0.3999999999999999,
5.4
],
"squared": [
6.760000000000001,
2.5600000000000005,
2.5600000000000005,
0.15999999999999992,
29.160000000000004
]
}/**
* Fintech Math Bootcamp · Lesson 041 of 120
* Deviation, Absolute Deviation, and Squared Deviation
* Module 05: Dispersion, Shape, and Robust Statistics
*
* Scenario: Explaining inconsistent settlement time
* Rule: deviation = x − center; magnitude = |deviation|; square = deviation²
*
* Try it: Are squared deviations still measured in hours?
*
* Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/dispersion-shape-and-robust-statistics/deviation-absolute-deviation-and-squared-deviation/
* Free course: https://courses.thefintechbuilder.com
* Synthetic teaching example, not financial advice or a production library.
*/
#include <charconv>
#include <cmath>
#include <iostream>
#include <string>
#include <utility>
#include <vector>
// --- Minimal JSON value and printer: objects keep insertion order, 2-space indent. ---
struct Json {
enum class Kind { Null, Number, Text, Array, Object };
Kind kind = Kind::Null;
double number = 0;
std::string text;
std::vector<std::string> keys; // object keys, parallel to items
std::vector<Json> items; // array elements or object values
};
Json num(double v) { Json j; j.kind = Json::Kind::Number; j.number = v; return j; }
Json str(const std::string& s) { Json j; j.kind = Json::Kind::Text; j.text = s; return j; }
Json arr(const std::vector<Json>& values) { Json j; j.kind = Json::Kind::Array; j.items = values; return j; }
Json arr(const std::vector<double>& values) {
std::vector<Json> items;
for (double v : values) items.push_back(num(v));
return arr(items);
}
Json obj(const std::vector<std::pair<std::string, Json>>& fields) {
Json j;
j.kind = Json::Kind::Object;
for (const auto& [key, value] : fields) { j.keys.push_back(key); j.items.push_back(value); }
return j;
}
std::string formatNumber(double v) {
if (!std::isfinite(v)) return "null";
char buf[64];
auto end = std::to_chars(buf, buf + sizeof buf, v).ptr; // shortest round-trip form
return std::string(buf, end);
}
void writeJson(std::ostream& out, const Json& j, const std::string& indent) {
switch (j.kind) {
case Json::Kind::Null: out << "null"; return;
case Json::Kind::Number: out << formatNumber(j.number); return;
case Json::Kind::Text: out << '"' << j.text << '"'; return;
default: break;
}
bool isObject = j.kind == Json::Kind::Object;
if (j.items.empty()) { out << (isObject ? "{}" : "[]"); return; }
std::string inner = indent + " ";
out << (isObject ? "{\n" : "[\n");
for (size_t i = 0; i < j.items.size(); ++i) {
out << inner;
if (isObject) out << '"' << j.keys[i] << "\": ";
writeJson(out, j.items[i], inner);
out << (i + 1 < j.items.size() ? ",\n" : "\n");
}
out << indent << (isObject ? '}' : ']');
}
// --- Lesson ---
Json lesson041() {
const std::vector<double> hours = {1, 2, 2, 4, 9};
const double center = 3.6;
std::vector<double> deviations, absolute, squared;
for (double x : hours) {
double d = x - center;
deviations.push_back(d);
absolute.push_back(std::abs(d));
squared.push_back(d * d);
}
return obj({{"deviations", arr(deviations)}, {"absolute", arr(absolute)}, {"squared", arr(squared)}});
}
int main() {
writeJson(std::cout, lesson041(), "");
std::cout << '\n';
}
No browser runner for C++ yet
Read the code here, then run it in your own toolchain or a ready-made cloud workspace.
Expected output
{
"deviations": [
-2.6,
-1.6,
-1.6,
0.3999999999999999,
5.4
],
"absolute": [
2.6,
1.6,
1.6,
0.3999999999999999,
5.4
],
"squared": [
6.760000000000001,
2.5600000000000005,
2.5600000000000005,
0.15999999999999992,
29.160000000000004
]
}// Fintech Math Bootcamp · Lesson 041 of 120
// Deviation, Absolute Deviation, and Squared Deviation
// Module 05: Dispersion, Shape, and Robust Statistics
//
// Scenario: Explaining inconsistent settlement time
// Rule: deviation = x − center; magnitude = |deviation|; square = deviation²
//
// Try it: Are squared deviations still measured in hours?
//
// Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/dispersion-shape-and-robust-statistics/deviation-absolute-deviation-and-squared-deviation/
// Free course: https://courses.thefintechbuilder.com
// Synthetic teaching example, not financial advice or a production library.
// --- Minimal JSON value and printer: objects keep insertion order, 2-space indent. ---
#[allow(dead_code)]
enum Json {
Null,
Num(f64),
Str(String),
Arr(Vec<Json>),
Obj(Vec<(String, Json)>),
}
#[allow(dead_code)]
fn nums(values: &[f64]) -> Json {
Json::Arr(values.iter().map(|&v| Json::Num(v)).collect())
}
#[allow(dead_code)]
fn obj(fields: Vec<(&str, Json)>) -> Json {
Json::Obj(fields.into_iter().map(|(k, v)| (k.to_string(), v)).collect())
}
fn format_number(v: f64) -> String {
if !v.is_finite() {
return "null".to_string();
}
if v.fract() == 0.0 && v.abs() < 1e15 {
return format!("{}", v as i64);
}
format!("{:?}", v) // shortest round-trip form
}
impl Json {
fn render(&self, indent: &str) -> String {
let inner = format!("{} ", indent);
match self {
Json::Null => "null".to_string(),
Json::Num(v) => format_number(*v),
Json::Str(s) => format!("\"{}\"", s),
Json::Arr(items) if items.is_empty() => "[]".to_string(),
Json::Obj(fields) if fields.is_empty() => "{}".to_string(),
Json::Arr(items) => {
let lines: Vec<String> = items.iter().map(|v| format!("{}{}", inner, v.render(&inner))).collect();
format!("[\n{}\n{}]", lines.join(",\n"), indent)
}
Json::Obj(fields) => {
let lines: Vec<String> = fields
.iter()
.map(|(k, v)| format!("{}\"{}\": {}", inner, k, v.render(&inner)))
.collect();
format!("{{\n{}\n{}}}", lines.join(",\n"), indent)
}
}
}
}
// --- Lesson ---
fn lesson041() -> Json {
let (hours, center): ([f64; 5], f64) = ([1.0, 2.0, 2.0, 4.0, 9.0], 3.6);
let deviations: Vec<f64> = hours.iter().map(|&x| x - center).collect();
let absolute: Vec<f64> = deviations.iter().map(|d| d.abs()).collect();
let squared: Vec<f64> = deviations.iter().map(|d| d * d).collect();
obj(vec![
("deviations", nums(&deviations)),
("absolute", nums(&absolute)),
("squared", nums(&squared)),
])
}
fn main() {
println!("{}", lesson041().render(""));
}
No browser runner for Rust yet
Read the code here, then run it in your own toolchain or a ready-made cloud workspace.
Expected output
{
"deviations": [
-2.6,
-1.6,
-1.6,
0.3999999999999999,
5.4
],
"absolute": [
2.6,
1.6,
1.6,
0.3999999999999999,
5.4
],
"squared": [
6.760000000000001,
2.5600000000000005,
2.5600000000000005,
0.15999999999999992,
29.160000000000004
]
}/**
* Fintech Math Bootcamp · Lesson 041 of 120
* Deviation, Absolute Deviation, and Squared Deviation
* Module 05: Dispersion, Shape, and Robust Statistics
*
* Scenario: Explaining inconsistent settlement time
* Rule: deviation = x − center; magnitude = |deviation|; square = deviation²
*
* Try it: Are squared deviations still measured in hours?
*
* Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/dispersion-shape-and-robust-statistics/deviation-absolute-deviation-and-squared-deviation/
* Free course: https://courses.thefintechbuilder.com
* Synthetic teaching example, not financial advice or a production library.
*/
using System;
using System.Linq;
using System.Text.Json;
var options = new JsonSerializerOptions { WriteIndented = true };
Console.WriteLine(JsonSerializer.Serialize(Lesson041(), options));
static object Lesson041()
{
double[] hours = { 1, 2, 2, 4, 9 };
double center = 3.6;
double[] deviations = hours.Select(x => x - center).ToArray();
return new
{
deviations,
absolute = deviations.Select(d => Math.Abs(d)).ToArray(),
squared = deviations.Select(d => d * d).ToArray(),
};
}
No browser runner for C# yet
Read the code here, then run it in your own toolchain or a ready-made cloud workspace.
Expected output
{
"deviations": [
-2.6,
-1.6,
-1.6,
0.3999999999999999,
5.4
],
"absolute": [
2.6,
1.6,
1.6,
0.3999999999999999,
5.4
],
"squared": [
6.760000000000001,
2.5600000000000005,
2.5600000000000005,
0.15999999999999992,
29.160000000000004
]
}Prefer your own machine? Every file is in the course repository · open it in Codespaces.
Lesson notes
The rule
deviation = x − center; magnitude = |deviation|; square = deviation²