Module 7 · Probability Distributions and Simulation Basics Lesson 62 of 120
Bernoulli and Binomial Distributions
Counting failures across a fixed number of comparable attempts.
Transcript
19 sentences · select one to jump thereCheck your understanding
Why is exactly two failures multiplied by three?
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 062 of 120
* Bernoulli and Binomial Distributions
* Module 07: Probability Distributions and Simulation Basics
*
* Scenario: Counting failures across a fixed number of comparable attempts
* Rule: K ~ Binomial(n,p); E[K]=np; Var(K)=np(1−p)
*
* Try it: Why is exactly two failures multiplied by three?
*
* Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/probability-distributions-and-simulation-basics/bernoulli-and-binomial-distributions/
* Free course: https://courses.thefintechbuilder.com
* Synthetic teaching example, not financial advice or a production library.
*/
export function lesson062() {
const n=3,p=.2,k=2;
const choose=(n:number,k:number)=>{let c=1;for(let i=1;i<=k;i++)c=c*(n-k+i)/i;return c;};
const exactlyTwo=choose(n,k)*p**k*(1-p)**(n-k);
const result={exactlyTwo,atLeastOne:1-(1-p)**n,
mean:n*p,variance:n*p*(1-p)};
return result;
}
export const checkedResult = {"exactlyTwo":0.09600000000000003,"atLeastOne":0.4879999999999999,"mean":0.6000000000000001,"variance":0.4800000000000001};
// Run this file directly: npx tsx lessons/07-probability-distributions-and-simulation-basics/062-bernoulli-and-binomial-distributions.ts
if (process.argv[1] && import.meta.url.endsWith(process.argv[1].replace(/\\/g, "/").split("/").pop()!)) {
console.log(JSON.stringify(lesson062(), null, 2));
}
Your output
Press Run to execute the code in your browser.
Expected output
{
"exactlyTwo": 0.09600000000000003,
"atLeastOne": 0.4879999999999999,
"mean": 0.6000000000000001,
"variance": 0.4800000000000001
}"""
Fintech Math Bootcamp · Lesson 062 of 120
Bernoulli and Binomial Distributions
Module 07: Probability Distributions and Simulation Basics
Scenario: Counting failures across a fixed number of comparable attempts
Rule: K ~ Binomial(n,p); E[K]=np; Var(K)=np(1−p)
Try it: Why is exactly two failures multiplied by three?
Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/probability-distributions-and-simulation-basics/bernoulli-and-binomial-distributions/
Free course: https://courses.thefintechbuilder.com
Synthetic teaching example, not financial advice or a production library.
"""
import json
def choose(n, k):
c = 1
for i in range(1, k + 1):
c = c * (n - k + i) / i
return c
def lesson_062():
n, p, k = 3, 0.2, 2
exactly_two = choose(n, k) * p**k * (1 - p) ** (n - k)
return {
"exactlyTwo": exactly_two,
"atLeastOne": 1 - (1 - p) ** n,
"mean": n * p,
"variance": n * p * (1 - p),
}
if __name__ == "__main__":
print(json.dumps(lesson_062(), indent=2))
Your output
Press Run to execute the code in your browser.
Expected output
{
"exactlyTwo": 0.09600000000000003,
"atLeastOne": 0.4879999999999999,
"mean": 0.6000000000000001,
"variance": 0.4800000000000001
}// Fintech Math Bootcamp - Lesson 062 of 120
// Bernoulli and Binomial Distributions
// Module 07: Probability Distributions and Simulation Basics
//
// Scenario: Counting failures across a fixed number of comparable attempts
// Rule: K ~ Binomial(n,p); E[K]=np; Var(K)=np(1-p)
//
// Try it: Why is exactly two failures multiplied by three?
//
// Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/probability-distributions-and-simulation-basics/bernoulli-and-binomial-distributions/
// Free course: https://courses.thefintechbuilder.com
// Synthetic teaching example, not financial advice or a production library.
import java.util.ArrayList;
import java.util.Arrays;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
public class Main {
// Binomial coefficient n choose k
static double choose(int n, int k) {
double c = 1;
for (int i = 1; i <= k; i++) {
c = c * (n - k + i) / i;
}
return c;
}
static Map<String, Object> lesson062() {
int n = 3;
double p = 0.2;
int k = 2;
double exactlyTwo = choose(n, k) * Math.pow(p, k) * Math.pow(1 - p, n - k);
Map<String, Object> result = new LinkedHashMap<String, Object>();
result.put("exactlyTwo", exactlyTwo);
result.put("atLeastOne", 1 - Math.pow(1 - p, n));
result.put("mean", n * p);
result.put("variance", n * p * (1 - p));
return result;
}
public static void main(String[] args) {
System.out.println(toJson(lesson062(), ""));
}
// Minimal JSON writer: two-space indent, whole numbers without a decimal point, NaN as null.
static String toJson(Object value, String indent) {
if (value == null) return "null";
if (value instanceof Boolean) return value.toString();
if (value instanceof Number) return formatNumber(((Number) value).doubleValue());
if (value instanceof String) return quote((String) value);
if (value instanceof double[]) {
List<Object> boxed = new ArrayList<Object>();
for (double d : (double[]) value) boxed.add(d);
return toJson(boxed, indent);
}
if (value instanceof Object[]) return toJson(Arrays.asList((Object[]) value), indent);
String inner = indent + " ";
StringBuilder out = new StringBuilder();
if (value instanceof Map) {
Map<?, ?> map = (Map<?, ?>) value;
if (map.isEmpty()) return "{}";
out.append("{\n");
int i = 0;
for (Map.Entry<?, ?> entry : map.entrySet()) {
out.append(inner).append(quote(entry.getKey().toString())).append(": ")
.append(toJson(entry.getValue(), inner));
out.append(++i < map.size() ? ",\n" : "\n");
}
return out.append(indent).append("}").toString();
}
List<?> list = (List<?>) value;
if (list.isEmpty()) return "[]";
out.append("[\n");
for (int i = 0; i < list.size(); i++) {
out.append(inner).append(toJson(list.get(i), inner));
out.append(i + 1 < list.size() ? ",\n" : "\n");
}
return out.append(indent).append("]").toString();
}
static String formatNumber(double x) {
if (Double.isNaN(x) || Double.isInfinite(x)) return "null";
if (x == Math.rint(x) && Math.abs(x) < 1e15) return Long.toString((long) x);
return Double.toString(x);
}
static String quote(String s) {
StringBuilder out = new StringBuilder("\"");
for (char c : s.toCharArray()) {
if (c == '"' || c == '\\') out.append('\\').append(c);
else if (c == '\n') out.append("\\n");
else if (c < 0x20) out.append(String.format("\\u%04x", (int) c));
else out.append(c);
}
return out.append('"').toString();
}
}
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
{
"exactlyTwo": 0.09600000000000003,
"atLeastOne": 0.4879999999999999,
"mean": 0.6000000000000001,
"variance": 0.4800000000000001
}// Fintech Math Bootcamp · Lesson 062 of 120
// Bernoulli and Binomial Distributions
// Module 07: Probability Distributions and Simulation Basics
//
// Scenario: Counting failures across a fixed number of comparable attempts
// Rule: K ~ Binomial(n,p); E[K]=np; Var(K)=np(1−p)
//
// Try it: Why is exactly two failures multiplied by three?
//
// Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/probability-distributions-and-simulation-basics/bernoulli-and-binomial-distributions/
// Free course: https://courses.thefintechbuilder.com
// Synthetic teaching example, not financial advice or a production library.
package main
import (
"encoding/json"
"fmt"
"math"
)
type Lesson062Result struct {
ExactlyTwo float64 `json:"exactlyTwo"`
AtLeastOne float64 `json:"atLeastOne"`
Mean float64 `json:"mean"`
Variance float64 `json:"variance"`
}
// choose returns the binomial coefficient n choose k.
func choose(n, k int) float64 {
c := 1.0
for i := 1; i <= k; i++ {
c = c * float64(n-k+i) / float64(i)
}
return c
}
func lesson062() Lesson062Result {
n, p, k := 3, 0.2, 2
exactlyTwo := choose(n, k) * math.Pow(p, float64(k)) * math.Pow(1-p, float64(n-k))
return Lesson062Result{
ExactlyTwo: exactlyTwo,
AtLeastOne: 1 - math.Pow(1-p, float64(n)),
Mean: float64(n) * p,
Variance: float64(n) * p * (1 - p),
}
}
func main() {
out, err := json.MarshalIndent(lesson062(), "", " ")
if err != nil {
panic(err)
}
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
{
"exactlyTwo": 0.09600000000000003,
"atLeastOne": 0.4879999999999999,
"mean": 0.6000000000000001,
"variance": 0.4800000000000001
}// Fintech Math Bootcamp · Lesson 062 of 120
// Bernoulli and Binomial Distributions
// Module 07: Probability Distributions and Simulation Basics
//
// Scenario: Counting failures across a fixed number of comparable attempts
// Rule: K ~ Binomial(n,p); E[K]=np; Var(K)=np(1−p)
//
// Try it: Why is exactly two failures multiplied by three?
//
// Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/probability-distributions-and-simulation-basics/bernoulli-and-binomial-distributions/
// Free course: https://courses.thefintechbuilder.com
// Synthetic teaching example, not financial advice or a production library.
#include <cmath>
#include <cstdio>
#include <cstdlib>
#include <iostream>
#include <optional>
#include <stdexcept>
#include <string>
#include <utility>
#include <vector>
// A minimal JSON value, enough to print this lesson's result.
struct Json {
enum class Kind { Null, Bool, Number, String, Array, Object };
Kind kind = Kind::Null;
bool flag = false;
double number = 0.0;
std::string text;
std::vector<std::string> keys; // object keys, parallel to items
std::vector<Json> items; // array elements or object values
Json() = default;
Json(bool value) : kind(Kind::Bool), flag(value) {}
Json(int value) : kind(Kind::Number), number(value) {}
Json(double value) : kind(Kind::Number), number(value) {}
Json(const char* value) : kind(Kind::String), text(value) {}
Json(const std::string& value) : kind(Kind::String), text(value) {}
Json(const std::vector<double>& values) : kind(Kind::Array) {
for (double v : values) items.push_back(Json(v));
}
};
Json jsonArray(const std::vector<Json>& values) {
Json array;
array.kind = Json::Kind::Array;
array.items = values;
return array;
}
Json jsonObject(const std::vector<std::pair<std::string, Json>>& fields) {
Json object;
object.kind = Json::Kind::Object;
for (const auto& field : fields) {
object.keys.push_back(field.first);
object.items.push_back(field.second);
}
return object;
}
// Shortest decimal form that reads back as the same double.
std::string formatNumber(double x) {
if (!std::isfinite(x)) return "null";
char buffer[32];
if (x == std::floor(x) && std::fabs(x) < 1e15) {
std::snprintf(buffer, sizeof buffer, "%.0f", x);
return buffer;
}
for (int precision = 1; precision <= 17; ++precision) {
std::snprintf(buffer, sizeof buffer, "%.*g", precision, x);
if (std::strtod(buffer, nullptr) == x) break;
}
return buffer;
}
std::string quote(const std::string& s) {
std::string out = "\"";
for (char c : s) {
if (c == '"' || c == '\\') { out += '\\'; out += c; }
else if (c == '\n') out += "\\n";
else out += c;
}
return out + "\"";
}
std::string toJson(const Json& value, const std::string& indent = "") {
switch (value.kind) {
case Json::Kind::Null: return "null";
case Json::Kind::Bool: return value.flag ? "true" : "false";
case Json::Kind::Number: return formatNumber(value.number);
case Json::Kind::String: return quote(value.text);
default: break;
}
const bool isObject = value.kind == Json::Kind::Object;
if (value.items.empty()) return isObject ? "{}" : "[]";
const std::string inner = indent + " ";
std::string out = isObject ? "{\n" : "[\n";
for (std::size_t i = 0; i < value.items.size(); ++i) {
out += inner;
if (isObject) out += quote(value.keys[i]) + ": ";
out += toJson(value.items[i], inner);
out += i + 1 < value.items.size() ? ",\n" : "\n";
}
return out + indent + (isObject ? "}" : "]");
}
// Binomial coefficient n choose k
double choose(int n, int k) {
double c = 1.0;
for (int i = 1; i <= k; ++i) c = c * (n - k + i) / i;
return c;
}
Json lesson062() {
const int n = 3;
const double p = 0.2;
const int k = 2;
const double exactlyTwo = choose(n, k) * std::pow(p, k) * std::pow(1 - p, n - k);
return jsonObject({
{"exactlyTwo", exactlyTwo},
{"atLeastOne", 1 - std::pow(1 - p, n)},
{"mean", n * p},
{"variance", n * p * (1 - p)},
});
}
int main() {
std::cout << toJson(lesson062()) << '\n';
return 0;
}
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
{
"exactlyTwo": 0.09600000000000003,
"atLeastOne": 0.4879999999999999,
"mean": 0.6000000000000001,
"variance": 0.4800000000000001
}// Fintech Math Bootcamp · Lesson 062 of 120
// Bernoulli and Binomial Distributions
// Module 07: Probability Distributions and Simulation Basics
//
// Scenario: Counting failures across a fixed number of comparable attempts
// Rule: K ~ Binomial(n,p); E[K]=np; Var(K)=np(1−p)
//
// Try it: Why is exactly two failures multiplied by three?
//
// Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/probability-distributions-and-simulation-basics/bernoulli-and-binomial-distributions/
// Free course: https://courses.thefintechbuilder.com
// Synthetic teaching example, not financial advice or a production library.
/// A minimal JSON value, enough to print this lesson's result.
#[allow(dead_code)]
enum Json {
Null,
Bool(bool),
Num(f64),
Str(String),
Arr(Vec<Json>),
Obj(Vec<(String, Json)>),
}
#[allow(dead_code)]
impl Json {
fn obj(fields: Vec<(&str, Json)>) -> Json {
Json::Obj(fields.into_iter().map(|(k, v)| (k.to_string(), v)).collect())
}
fn nums(values: &[f64]) -> Json {
Json::Arr(values.iter().map(|&v| Json::Num(v)).collect())
}
/// Pretty-prints with two-space indentation.
fn pretty(&self, indent: &str) -> String {
let inner = format!("{} ", indent);
match self {
Json::Null => "null".to_string(),
Json::Bool(b) => b.to_string(),
Json::Num(x) => format_number(*x),
Json::Str(s) => quote(s),
Json::Arr(items) if items.is_empty() => "[]".to_string(),
Json::Obj(fields) if fields.is_empty() => "{}".to_string(),
Json::Arr(items) => {
let body: Vec<String> = items
.iter()
.map(|v| format!("{}{}", inner, v.pretty(&inner)))
.collect();
format!("[\n{}\n{}]", body.join(",\n"), indent)
}
Json::Obj(fields) => {
let body: Vec<String> = fields
.iter()
.map(|(k, v)| format!("{}{}: {}", inner, quote(k), v.pretty(&inner)))
.collect();
format!("{{\n{}\n{}}}", body.join(",\n"), indent)
}
}
}
}
fn format_number(x: f64) -> String {
if !x.is_finite() {
"null".to_string()
} else if x == x.trunc() && x.abs() < 1e15 {
format!("{}", x as i64)
} else {
format!("{}", x)
}
}
fn quote(s: &str) -> String {
let mut out = String::from("\"");
for c in s.chars() {
match c {
'"' => out.push_str("\\\""),
'\\' => out.push_str("\\\\"),
'\n' => out.push_str("\\n"),
c => out.push(c),
}
}
out.push('"');
out
}
/// Binomial coefficient n choose k.
fn choose(n: u32, k: u32) -> f64 {
let mut c = 1.0;
for i in 1..=k {
c = c * f64::from(n - k + i) / f64::from(i);
}
c
}
fn lesson_062() -> Json {
let (n, p, k) = (3u32, 0.2_f64, 2u32);
let exactly_two = choose(n, k) * p.powf(f64::from(k)) * (1.0 - p).powf(f64::from(n - k));
Json::obj(vec![
("exactlyTwo", Json::Num(exactly_two)),
("atLeastOne", Json::Num(1.0 - (1.0 - p).powf(f64::from(n)))),
("mean", Json::Num(f64::from(n) * p)),
("variance", Json::Num(f64::from(n) * p * (1.0 - p))),
])
}
fn main() {
println!("{}", lesson_062().pretty(""));
}
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
{
"exactlyTwo": 0.09600000000000003,
"atLeastOne": 0.4879999999999999,
"mean": 0.6000000000000001,
"variance": 0.4800000000000001
}// Fintech Math Bootcamp · Lesson 062 of 120
// Bernoulli and Binomial Distributions
// Module 07: Probability Distributions and Simulation Basics
//
// Scenario: Counting failures across a fixed number of comparable attempts
// Rule: K ~ Binomial(n,p); E[K]=np; Var(K)=np(1−p)
//
// Try it: Why is exactly two failures multiplied by three?
//
// Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/probability-distributions-and-simulation-basics/bernoulli-and-binomial-distributions/
// Free course: https://courses.thefintechbuilder.com
// Synthetic teaching example, not financial advice or a production library.
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text.Json;
var options = new JsonSerializerOptions { WriteIndented = true };
Console.WriteLine(JsonSerializer.Serialize(Lesson062(), options));
// Binomial coefficient n choose k
static double Choose(int n, int k)
{
double c = 1;
for (int i = 1; i <= k; i++) c = c * (n - k + i) / i;
return c;
}
static object Lesson062()
{
int n = 3, k = 2;
double p = 0.2;
double exactlyTwo = Choose(n, k) * Math.Pow(p, k) * Math.Pow(1 - p, n - k);
return new
{
exactlyTwo,
atLeastOne = 1 - Math.Pow(1 - p, n),
mean = n * p,
variance = n * p * (1 - p),
};
}
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
{
"exactlyTwo": 0.09600000000000003,
"atLeastOne": 0.4879999999999999,
"mean": 0.6000000000000001,
"variance": 0.4800000000000001
}Prefer your own machine? Every file is in the course repository · open it in Codespaces.
Lesson notes
The rule
K ~ Binomial(n,p); E[K]=np; Var(K)=np(1−p)