Weighted Mean

/**
 * Fintech Math Bootcamp · Lesson 033 of 120
 * Weighted Mean
 * Module 04: Location, Ranking, and Exploratory Summaries
 *
 * Scenario: Pooling merchant approval rates by exposure
 * Rule:     weighted mean = Σ(wᵢxᵢ)/Σwᵢ
 *
 * Try it:   Which figure describes all 1,000 attempts combined?
 *
 * Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/location-ranking-and-exploratory-summaries/weighted-mean/
 * Free course:    https://courses.thefintechbuilder.com
 * Synthetic teaching example, not financial advice or a production library.
 */

export function lesson033() {
  const rates = [0.90, 0.50];
  const attempts = [100, 900];
  const weighted = rates.reduce((s,r,i) => s+r*attempts[i],0)
    / attempts.reduce((s,n) => s+n,0);
  const result = {unweighted: (rates[0]+rates[1])/2, weighted};
  return result;
}

export const checkedResult = {"unweighted":0.7,"weighted":0.54};

// Run this file directly: npx tsx lessons/04-location-ranking-and-exploratory-summaries/033-weighted-mean.ts
if (process.argv[1] && import.meta.url.endsWith(process.argv[1].replace(/\\/g, "/").split("/").pop()!)) {
  console.log(JSON.stringify(lesson033(), null, 2));
}

# Fintech Math Bootcamp · Lesson 033 of 120
# Weighted Mean
# Module 04: Location, Ranking, and Exploratory Summaries
#
# Scenario: Pooling merchant approval rates by exposure
# Rule:     weighted mean = Σ(wᵢxᵢ)/Σwᵢ
#
# Try it:   Which figure describes all 1,000 attempts combined?
#
# Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/location-ranking-and-exploratory-summaries/weighted-mean/
# Free course:    https://courses.thefintechbuilder.com
# Synthetic teaching example, not financial advice or a production library.

import json


def lesson033() -> dict:
    rates = [0.90, 0.50]
    attempts = [100, 900]
    weighted = sum(r * n for r, n in zip(rates, attempts)) / sum(attempts)
    return {"unweighted": (rates[0] + rates[1]) / 2, "weighted": weighted}


if __name__ == "__main__":
    print(json.dumps(lesson033(), indent=2))

/**
 * Fintech Math Bootcamp · Lesson 033 of 120
 * Weighted Mean
 * Module 04: Location, Ranking, and Exploratory Summaries
 *
 * Scenario: Pooling merchant approval rates by exposure
 * Rule:     weighted mean = Σ(wᵢxᵢ)/Σwᵢ
 *
 * Try it:   Which figure describes all 1,000 attempts combined?
 *
 * Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/location-ranking-and-exploratory-summaries/weighted-mean/
 * 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> lesson033() {
        double[] rates = {0.90, 0.50};
        double[] attempts = {100, 900};
        double numerator = 0, totalAttempts = 0;
        for (int i = 0; i < rates.length; i++) {
            numerator += rates[i] * attempts[i];
            totalAttempts += attempts[i];
        }
        Map<String, Object> result = new LinkedHashMap<String, Object>();
        result.put("unweighted", (rates[0] + rates[1]) / 2);
        result.put("weighted", numerator / totalAttempts);
        return result;
    }

    public static void main(String[] args) {
        System.out.println(toJson(lesson033(), ""));
    }

    // --- 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);
    }
}

// Fintech Math Bootcamp · Lesson 033 of 120
// Weighted Mean
// Module 04: Location, Ranking, and Exploratory Summaries
//
// Scenario: Pooling merchant approval rates by exposure
// Rule:     weighted mean = Σ(wᵢxᵢ)/Σwᵢ
//
// Try it:   Which figure describes all 1,000 attempts combined?
//
// Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/location-ranking-and-exploratory-summaries/weighted-mean/
// Free course:    https://courses.thefintechbuilder.com
// Synthetic teaching example, not financial advice or a production library.

package main

import (
	"encoding/json"
	"fmt"
)

// PooledRates compares a plain average of rates with the attempt-weighted rate.
type PooledRates struct {
	Unweighted float64 `json:"unweighted"`
	Weighted   float64 `json:"weighted"`
}

func lesson033() PooledRates {
	rates := []float64{0.90, 0.50}
	attempts := []float64{100, 900}
	numerator, totalAttempts := 0.0, 0.0
	for i, r := range rates {
		numerator += r * attempts[i]
		totalAttempts += attempts[i]
	}
	return PooledRates{
		Unweighted: (rates[0] + rates[1]) / 2,
		Weighted:   numerator / totalAttempts,
	}
}

func main() {
	out, _ := json.MarshalIndent(lesson033(), "", "  ")
	fmt.Println(string(out))
}

/**
 * Fintech Math Bootcamp · Lesson 033 of 120
 * Weighted Mean
 * Module 04: Location, Ranking, and Exploratory Summaries
 *
 * Scenario: Pooling merchant approval rates by exposure
 * Rule:     weighted mean = Σ(wᵢxᵢ)/Σwᵢ
 *
 * Try it:   Which figure describes all 1,000 attempts combined?
 *
 * Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/location-ranking-and-exploratory-summaries/weighted-mean/
 * 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 lesson033() {
    const std::vector<double> rates = {0.90, 0.50};
    const std::vector<double> attempts = {100, 900};
    double numerator = 0, totalAttempts = 0;
    for (size_t i = 0; i < rates.size(); ++i) {
        numerator += rates[i] * attempts[i];
        totalAttempts += attempts[i];
    }
    return obj({
        {"unweighted", num((rates[0] + rates[1]) / 2)},
        {"weighted", num(numerator / totalAttempts)},
    });
}

int main() {
    writeJson(std::cout, lesson033(), "");
    std::cout << '\n';
}

// Fintech Math Bootcamp · Lesson 033 of 120
// Weighted Mean
// Module 04: Location, Ranking, and Exploratory Summaries
//
// Scenario: Pooling merchant approval rates by exposure
// Rule:     weighted mean = Σ(wᵢxᵢ)/Σwᵢ
//
// Try it:   Which figure describes all 1,000 attempts combined?
//
// Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/location-ranking-and-exploratory-summaries/weighted-mean/
// 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 lesson033() -> Json {
    let rates: [f64; 2] = [0.90, 0.50];
    let attempts: [f64; 2] = [100.0, 900.0];
    let numerator: f64 = rates.iter().zip(attempts.iter()).map(|(r, n)| r * n).sum();
    let total_attempts: f64 = attempts.iter().sum();
    obj(vec![
        ("unweighted", Json::Num((rates[0] + rates[1]) / 2.0)),
        ("weighted", Json::Num(numerator / total_attempts)),
    ])
}

fn main() {
    println!("{}", lesson033().render(""));
}

/**
 * Fintech Math Bootcamp · Lesson 033 of 120
 * Weighted Mean
 * Module 04: Location, Ranking, and Exploratory Summaries
 *
 * Scenario: Pooling merchant approval rates by exposure
 * Rule:     weighted mean = Σ(wᵢxᵢ)/Σwᵢ
 *
 * Try it:   Which figure describes all 1,000 attempts combined?
 *
 * Lesson article: https://thefintechbuilder.com/financial-mathematics-statistics-and-data-foundations/location-ranking-and-exploratory-summaries/weighted-mean/
 * 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(Lesson033(), options));

static object Lesson033()
{
    double[] rates = { 0.90, 0.50 };
    double[] attempts = { 100, 900 };
    double weighted = rates.Select((r, i) => r * attempts[i]).Sum() / attempts.Sum();
    return new { unweighted = (rates[0] + rates[1]) / 2, weighted };
}