Acceptance Chance Calculator

Acceptance Chance Calculator: Estimate Your Likelihood :root { –primary-color: #004a99; –background-color: #f8f9fa; –card-background: #ffffff; –text-color: #333; –border-color: #ddd; –shadow-color: rgba(0, 0, 0, 0.1); } body { font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; background-color: var(–background-color); color: var(–text-color); margin: 0; padding: 0; line-height: 1.6; } .container { max-width: 960px; margin: 20px auto; padding: 20px; background-color: var(–card-background); border-radius: 8px; box-shadow: 0 2px 10px var(–shadow-color); } h1, h2, h3 { color: var(–primary-color); text-align: center; margin-bottom: 20px; } h1 { font-size: 2.2em; } h2 { font-size: 1.8em; margin-top: 30px; border-bottom: 2px solid var(–primary-color); padding-bottom: 5px; } h3 { font-size: 1.4em; margin-top: 25px; color: var(–text-color); } .calculator-section { margin-bottom: 40px; padding: 25px; border: 1px solid var(–border-color); border-radius: 8px; background-color: var(–card-background); 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Acceptance Chance Calculator

Estimate your likelihood of acceptance for various applications with our intuitive tool.

Acceptance Chance Calculator

Loan Application Credit Card Application Job Application Grant Application Select the type of application you are applying for.
Your FICO or equivalent credit score (e.g., 300-850).
Your total annual income before taxes.
Your total monthly debt payments divided by your gross monthly income.
The total amount you are requesting.
The duration of the loan in years.
Your FICO or equivalent credit score (e.g., 300-850).
Your total annual income before taxes.
Total credit used divided by total available credit.
How long your credit accounts have been open.
Years of experience directly related to the job.
High School Diploma Associate's Degree Bachelor's Degree Master's Degree Doctorate Your highest level of educational attainment.
Percentage of required skills you possess.
Your score from the job interview.
Score reflecting the potential positive impact of your project.
Years of experience relevant to the grant's purpose.
The amount of funding requested for the project.
Score reflecting how well the project aligns with grant objectives.

Your Estimated Acceptance Chance

–%

Key Assumptions:

Factors Influencing Acceptance

Visualizing the impact of key factors on your acceptance chance.
Comparison of Factors by Application Type
Factor Loan Application Credit Card Job Application Grant Application
Score/Rating Credit Score Credit Score Skills Match Alignment Score
Income/Value Annual Income Annual Income Relevant Experience Project Impact
Ratio/Metric Debt-to-Income Ratio Credit Utilization Education Level Applicant Experience
Amount/Term Loan Amount & Term Years of Credit History Interview Score Funding Need

Understanding Your Acceptance Chance

What is an acceptance chance calculator? An acceptance chance calculator is a sophisticated tool designed to provide an estimated probability of success for various types of applications. Whether you're applying for a loan, a credit card, a job, or a grant, understanding your likelihood of being approved is crucial for managing expectations and strategizing your approach. This calculator helps demystify the process by analyzing key input factors and translating them into a percentage chance of acceptance.

Acceptance Chance Calculator Formula and Mathematical Explanation

The core of the acceptance chance calculator relies on a weighted scoring model. Each input parameter is assigned a specific weight based on its general importance for a given application type. The formula can be broadly represented as:

Acceptance Chance (%) = Σ (Input Value * Weight) / Σ (Maximum Possible Input Value * Weight) * 100

For instance, in a loan application, a higher credit score and a lower debt-to-income ratio generally contribute positively to the acceptance chance. Each factor is normalized and then multiplied by its assigned weight. The sum of these weighted scores is then divided by the maximum possible weighted score to yield a probability percentage. The specific weights and scoring ranges are proprietary and adjusted based on industry standards and the type of application. For example, credit score might have a higher weight in credit card applications than in job applications. This calculator uses simplified models to provide a useful estimate, acknowledging that real-world decisions involve many nuanced factors.

Practical Examples (Real-World Use Cases)

Consider Sarah, who is applying for a personal loan. She has a credit score of 730, an annual income of $80,000, and a debt-to-income ratio of 30%. She needs a loan of $15,000 over 5 years. Plugging these figures into our Acceptance Chance Calculator, she might see an estimated acceptance chance of 85%. This suggests a strong likelihood of approval, encouraging her to proceed with the application.

In another scenario, John is applying for a software engineering job. He has 4 years of relevant experience, a Bachelor's degree, estimates his skills match at 75%, and received a 92% in his interview. The calculator might indicate a 70% chance of acceptance. This tells John that while he has a good chance, there might be areas where he could strengthen his profile or prepare further for potential follow-up stages. Understanding these probabilities helps individuals make informed decisions about where to invest their time and effort, potentially improving their outcomes by focusing on areas that significantly impact their loan approval odds.

How to Use This Acceptance Chance Calculator

Using the Acceptance Chance Calculator is straightforward:

  1. Select Application Type: Choose the category that best fits your situation (Loan, Credit Card, Job, Grant).
  2. Input Relevant Data: Fill in the fields that appear based on your selection. Provide accurate information such as credit scores, income, experience, or specific project details. Use the helper text for guidance on what each field requires.
  3. View Results: Click "Calculate Chance". The calculator will display your primary estimated acceptance chance percentage, along with key intermediate values and assumptions made by the model.
  4. Analyze Factors: Examine the chart and table to understand how different factors contribute to your overall chance and how they compare across application types.
  5. Reset or Copy: Use the "Reset" button to clear the fields and start over, or "Copy Results" to save your calculated data.

For optimal results, ensure all your inputs are accurate and reflect your current situation. This tool is designed to provide an estimate, and actual outcomes may vary. For more detailed insights into specific application types, consider exploring our credit card acceptance probability guide.

Key Factors That Affect Acceptance Chance Results

Several elements significantly influence your acceptance chance, varying by application type:

  • Creditworthiness (for Loans/Credit Cards): Your credit score, credit history length, credit utilization ratio, and payment history are paramount. Lenders use these to gauge your reliability in repaying borrowed funds. A strong credit profile significantly boosts your loan acceptance chance.
  • Financial Stability (for Loans/Credit Cards): Lenders assess your income, employment stability, and debt-to-income ratio to ensure you can afford the repayments.
  • Qualifications and Fit (for Jobs): Relevant experience, education, specific skills, and performance during the interview process are critical for job applications. A high skills match and strong interview performance increase your likelihood of job offer acceptance.
  • Project Merit and Alignment (for Grants): For grants, the potential impact of your project, its alignment with the grantor's mission, your experience, and the clarity of your proposal are key determinants.
  • Application Completeness and Accuracy: Submitting a complete, error-free application demonstrates attention to detail and seriousness, which can positively influence decision-makers.

Understanding these factors allows you to proactively improve your profile before applying.

Frequently Asked Questions (FAQ)

How accurate is the acceptance chance calculator?
This calculator provides an estimate based on common scoring models. Actual acceptance decisions involve many variables, including lender-specific criteria, market conditions, and subjective assessments. It's a guide, not a guarantee.
Can I improve my acceptance chance?
Yes. For financial applications, focus on improving your credit score, reducing debt, and ensuring stable income. For jobs, enhance relevant skills and gain experience. For grants, refine your project proposal and demonstrate strong alignment.
What is a good acceptance chance percentage?
Generally, a chance above 75% indicates a strong likelihood of acceptance. Chances between 50-75% suggest moderate probability, while below 50% indicates a lower chance, suggesting areas for improvement or alternative options.
Does the calculator consider all factors?
This calculator incorporates the most significant factors for each application type. However, real-world scenarios might include additional elements like employment history verification, background checks, or specific program requirements not captured here.
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var currentApplicationType = 'loan'; var chartInstance = null; var acceptanceChart = null; function updateCalculatorLogic() { var type = document.getElementById('applicationType').value; currentApplicationType = type; document.getElementById('loanInputs').style.display = (type === 'loan') ? 'block' : 'none'; document.getElementById('creditCardInputs').style.display = (type === 'creditCard') ? 'block' : 'none'; document.getElementById('jobInputs').style.display = (type === 'job') ? 'block' : 'none'; document.getElementById('grantInputs').style.display = (type === 'grant') ? 'block' : 'none'; resetErrorMessages(); clearResults(); calculateAcceptanceChance(); // Recalculate with new inputs updateChart(); // Update chart based on new type } function validateInput(id, min, max, isRequired = true) { var input = document.getElementById(id); var value = parseFloat(input.value); var errorElement = document.getElementById(id + 'Error'); var isValid = true; errorElement.innerText = "; errorElement.classList.remove('visible'); input.style.borderColor = '#ccc'; if (isRequired && (input.value === " || isNaN(value))) { errorElement.innerText = 'This field is required.'; errorElement.classList.add('visible'); input.style.borderColor = '#dc3545'; return false; } if (!isNaN(value)) { if (min !== null && value max) { errorElement.innerText = 'Value cannot be greater than ' + max + '.'; errorElement.classList.add('visible'); input.style.borderColor = '#dc3545'; isValid = false; } } return isValid; } function resetErrorMessages() { var inputs = document.querySelectorAll('.input-group input, .input-group select'); for (var i = 0; i < inputs.length; i++) { var input = inputs[i]; var errorElement = document.getElementById(input.id + 'Error'); if (errorElement) { errorElement.innerText = ''; errorElement.classList.remove('visible'); } input.style.borderColor = '#ccc'; } } function clearResults() { document.getElementById('resultsContainer').style.display = 'none'; document.getElementById('primaryResult').innerText = '–%'; document.getElementById('intermediateValue1').innerText = ''; document.getElementById('intermediateValue2').innerText = ''; document.getElementById('intermediateValue3').innerText = ''; document.getElementById('assumption1').innerText = ''; document.getElementById('assumption2').innerText = ''; document.getElementById('assumption3').innerText = ''; document.querySelector('.formula-explanation').innerText = ''; } function calculateAcceptanceChance() { resetErrorMessages(); var isValid = true; var inputs = {}; var results = {}; var assumptions = {}; var formula = ''; // — Input Validation — if (currentApplicationType === 'loan') { inputs.creditScore = parseFloat(document.getElementById('creditScoreLoan').value); inputs.income = parseFloat(document.getElementById('incomeLoan').value); inputs.dti = parseFloat(document.getElementById('debtToIncomeLoan').value); inputs.loanAmount = parseFloat(document.getElementById('loanAmount').value); inputs.loanTerm = parseFloat(document.getElementById('loanTerm').value); isValid &= validateInput('creditScoreLoan', 300, 850); isValid &= validateInput('incomeLoan', 0, null); isValid &= validateInput('debtToIncomeLoan', 0, 100); isValid &= validateInput('loanAmount', 0, null); isValid &= validateInput('loanTerm', 1, null); if (!isValid) return; // — Loan Calculation Logic — var scoreWeight = 0.4; var incomeWeight = 0.2; var dtiWeight = 0.25; var loanAmountWeight = 0.1; var loanTermWeight = 0.05; var normalizedScore = Math.max(0, Math.min(1, (inputs.creditScore – 300) / 550)); // Scale 300-850 to 0-1 var normalizedIncome = Math.min(1, inputs.income / 150000); // Cap at 150k for scaling var normalizedDti = Math.max(0, 1 – (inputs.dti / 60)); // Lower DTI is better, scale 0-60 to 0-1 var normalizedLoanAmount = Math.max(0, 1 – (inputs.loanAmount / 100000)); // Lower amount is better, scale up to 100k var normalizedLoanTerm = Math.max(0, 1 – (inputs.loanTerm / 30)); // Shorter term is better, scale up to 30 years var weightedScore = (normalizedScore * scoreWeight) + (normalizedIncome * incomeWeight) + (normalizedDti * dtiWeight) + (normalizedLoanAmount * loanAmountWeight) + (normalizedLoanTerm * loanTermWeight); results.chance = Math.min(98, Math.max(10, weightedScore * 100)); // Clamp between 10% and 98% results.intermediate1 = "Weighted Score: " + weightedScore.toFixed(3); results.intermediate2 = "Normalized Credit Score: " + normalizedScore.toFixed(2); results.intermediate3 = "Normalized DTI: " + normalizedDti.toFixed(2); assumptions.loanType = "Personal Loan"; assumptions.creditScoreImpact = "High"; assumptions.dtiImpact = "Significant"; formula = "Acceptance Chance is calculated using a weighted sum of normalized input factors (Credit Score, Income, DTI, Loan Amount, Loan Term). Higher scores and favorable ratios increase the chance."; } else if (currentApplicationType === 'creditCard') { inputs.creditScore = parseFloat(document.getElementById('creditScoreCard').value); inputs.income = parseFloat(document.getElementById('incomeCard').value); inputs.utilization = parseFloat(document.getElementById('creditUtilization').value); inputs.creditHistory = parseFloat(document.getElementById('yearsCreditHistory').value); isValid &= validateInput('creditScoreCard', 300, 850); isValid &= validateInput('incomeCard', 0, null); isValid &= validateInput('creditUtilization', 0, 100); isValid &= validateInput('yearsCreditHistory', 0, null); if (!isValid) return; // — Credit Card Calculation Logic — var scoreWeight = 0.45; var incomeWeight = 0.25; var utilizationWeight = 0.20; var historyWeight = 0.10; var normalizedScore = Math.max(0, Math.min(1, (inputs.creditScore – 300) / 550)); var normalizedIncome = Math.min(1, inputs.income / 100000); var normalizedUtilization = Math.max(0, 1 – (inputs.utilization / 30)); // Lower utilization is better, scale 0-30 to 0-1 var normalizedHistory = Math.min(1, inputs.creditHistory / 15); // Cap at 15 years for scaling var weightedScore = (normalizedScore * scoreWeight) + (normalizedIncome * incomeWeight) + (normalizedUtilization * utilizationWeight) + (normalizedHistory * historyWeight); results.chance = Math.min(97, Math.max(15, weightedScore * 100)); results.intermediate1 = "Weighted Score: " + weightedScore.toFixed(3); results.intermediate2 = "Normalized Credit Score: " + normalizedScore.toFixed(2); results.intermediate3 = "Normalized Utilization: " + normalizedUtilization.toFixed(2); assumptions.cardType = "General Credit Card"; assumptions.creditScoreImpact = "Very High"; assumptions.utilizationImpact = "Significant"; formula = "Acceptance Chance is based on a weighted model including Credit Score, Income, Credit Utilization, and Years of Credit History. Lower utilization and higher scores improve the odds."; } else if (currentApplicationType === 'job') { inputs.experience = parseFloat(document.getElementById('relevantExperience').value); inputs.education = document.getElementById('educationLevel').value; inputs.skillsMatch = parseFloat(document.getElementById('skillsMatch').value); inputs.interviewScore = parseFloat(document.getElementById('interviewScore').value); isValid &= validateInput('relevantExperience', 0, null); isValid &= validateInput('skillsMatch', 0, 100); isValid &= validateInput('interviewScore', 0, 100); if (!isValid) return; // — Job Calculation Logic — var experienceWeight = 0.30; var educationWeight = 0.15; var skillsWeight = 0.35; var interviewWeight = 0.20; var educationValue = 0; if (education === 'highSchool') educationValue = 0.5; else if (education === 'associate') educationValue = 0.7; else if (education === 'bachelor') educationValue = 0.9; else if (education === 'master') educationValue = 1.0; else if (education === 'doctorate') educationValue = 1.0; // Cap at doctorate var normalizedExperience = Math.min(1, inputs.experience / 10); // Cap at 10 years var normalizedSkills = inputs.skillsMatch / 100; var normalizedInterview = inputs.interviewScore / 100; var weightedScore = (normalizedExperience * experienceWeight) + (educationValue * educationWeight) + (normalizedSkills * skillsWeight) + (normalizedInterview * interviewWeight); results.chance = Math.min(95, Math.max(20, weightedScore * 100)); results.intermediate1 = "Weighted Score: " + weightedScore.toFixed(3); results.intermediate2 = "Normalized Experience: " + normalizedExperience.toFixed(2); results.intermediate3 = "Education Factor: " + educationValue.toFixed(1); assumptions.jobRole = "General Professional Role"; assumptions.experienceImpact = "High"; assumptions.skillsImpact = "Very High"; formula = "Acceptance Chance for jobs is estimated using weights for Relevant Experience, Education Level, Skills Match percentage, and Interview Score. Strong alignment in these areas increases the probability."; } else if (currentApplicationType === 'grant') { inputs.impactScore = parseFloat(document.getElementById('projectImpactScore').value); inputs.applicantExperience = parseFloat(document.getElementById('applicantExperience').value); inputs.fundingNeed = parseFloat(document.getElementById('fundingNeed').value); inputs.alignmentScore = parseFloat(document.getElementById('alignmentScore').value); isValid &= validateInput('projectImpactScore', 1, 10); isValid &= validateInput('applicantExperience', 0, null); isValid &= validateInput('fundingNeed', 0, null); isValid &= validateInput('alignmentScore', 1, 10); if (!isValid) return; // — Grant Calculation Logic — var impactWeight = 0.35; var applicantExpWeight = 0.20; var fundingNeedWeight = 0.15; // Can be complex, simpler model here var alignmentWeight = 0.30; var normalizedImpact = (inputs.impactScore – 1) / 9; // Scale 1-10 to 0-1 var normalizedApplicantExp = Math.min(1, inputs.applicantExperience / 20); // Cap at 20 years var normalizedFundingNeed = Math.max(0, 1 – (inputs.fundingNeed / 200000)); // Lower need relative to funder capacity is better, scale up to 200k var normalizedAlignment = (inputs.alignmentScore – 1) / 9; // Scale 1-10 to 0-1 var weightedScore = (normalizedImpact * impactWeight) + (normalizedApplicantExp * applicantExpWeight) + (normalizedFundingNeed * fundingNeedWeight) + (normalizedAlignment * alignmentWeight); results.chance = Math.min(96, Math.max(25, weightedScore * 100)); results.intermediate1 = "Weighted Score: " + weightedScore.toFixed(3); results.intermediate2 = "Normalized Impact Score: " + normalizedImpact.toFixed(2); results.intermediate3 = "Normalized Alignment Score: " + normalizedAlignment.toFixed(2); assumptions.grantType = "General Project Grant"; assumptions.impactWeight = "High"; assumptions.alignmentWeight = "High"; formula = "Grant acceptance chance is estimated based on Project Impact, Applicant Experience, Funding Need (relative), and Alignment Score with grant objectives. Strong impact and alignment are key."; } // — Display Results — document.getElementById('primaryResult').innerText = results.chance.toFixed(1) + '%'; document.getElementById('intermediateValue1').innerText = results.intermediate1 || ''; document.getElementById('intermediateValue2').innerText = results.intermediate2 || ''; document.getElementById('intermediateValue3').innerText = results.intermediate3 || ''; document.getElementById('assumption1').innerText = assumptions.loanType || assumptions.cardType || assumptions.jobRole || assumptions.grantType || 'N/A'; document.getElementById('assumption2').innerText = assumptions.creditScoreImpact || assumptions.creditScoreImpact || assumptions.experienceImpact || assumptions.impactWeight || 'N/A'; document.getElementById('assumption3').innerText = assumptions.dtiImpact || assumptions.utilizationImpact || assumptions.skillsImpact || assumptions.alignmentWeight || 'N/A'; document.querySelector('.formula-explanation').innerText = formula; document.getElementById('resultsContainer').style.display = 'block'; updateChart(); // Update chart data } function resetCalculator() { document.getElementById('applicationType').value = 'loan'; document.getElementById('creditScoreLoan').value = ''; document.getElementById('incomeLoan').value = ''; document.getElementById('debtToIncomeLoan').value = ''; document.getElementById('loanAmount').value = ''; document.getElementById('loanTerm').value = ''; document.getElementById('creditScoreCard').value = ''; document.getElementById('incomeCard').value = ''; document.getElementById('creditUtilization').value = ''; document.getElementById('yearsCreditHistory').value = ''; document.getElementById('relevantExperience').value = ''; document.getElementById('educationLevel').value = 'highSchool'; document.getElementById('skillsMatch').value = ''; document.getElementById('interviewScore').value = ''; document.getElementById('projectImpactScore').value = ''; document.getElementById('applicantExperience').value = ''; document.getElementById('fundingNeed').value = ''; document.getElementById('alignmentScore').value = ''; resetErrorMessages(); clearResults(); updateCalculatorLogic(); // Reset to default view and logic } function copyResults() { var primaryResult = document.getElementById('primaryResult').innerText; var intermediate1 = document.getElementById('intermediateValue1').innerText; var intermediate2 = document.getElementById('intermediateValue2').innerText; var intermediate3 = document.getElementById('intermediateValue3').innerText; var assumption1 = document.getElementById('assumption1').innerText; var assumption2 = document.getElementById('assumption2').innerText; var assumption3 = document.getElementById('assumption3').innerText; var formula = document.querySelector('.formula-explanation').innerText; var textToCopy = "Estimated Acceptance Chance: " + primaryResult + "\n\n"; if (intermediate1) textToCopy += intermediate1 + "\n"; if (intermediate2) textToCopy += intermediate2 + "\n"; if (intermediate3) textToCopy += intermediate3 + "\n\n"; textToCopy += "Key Assumptions:\n"; if (assumption1 !== 'N/A') textToCopy += "- " + assumption1 + "\n"; if (assumption2 !== 'N/A') textToCopy += "- " + assumption2 + "\n"; if (assumption3 !== 'N/A') textToCopy += "- " + assumption3 + "\n"; textToCopy += "\nFormula Used: " + formula; navigator.clipboard.writeText(textToCopy).then(function() { alert('Results copied to clipboard!'); }).catch(function(err) { console.error('Failed to copy: ', err); alert('Failed to copy results. Please copy manually.'); }); } function updateChart() { var ctx = document.getElementById('acceptanceChart').getContext('2d'); // Destroy previous chart instance if it exists if (chartInstance) { chartInstance.destroy(); } var labels = []; var data1 = []; // Primary Factor var data2 = []; // Secondary Factor if (currentApplicationType === 'loan') { labels = ['Credit Score', 'Income', 'Debt-to-Income Ratio', 'Loan Amount']; data1 = [0.4, 0.2, 0.25, 0.15]; // Weights data2 = [750, 80000, 30, 20000]; // Example Values } else if (currentApplicationType === 'creditCard') { labels = ['Credit Score', 'Income', 'Credit Utilization', 'Credit History']; data1 = [0.45, 0.25, 0.20, 0.10]; // Weights data2 = [720, 60000, 30, 7]; // Example Values } else if (currentApplicationType === 'job') { labels = ['Experience', 'Education', 'Skills Match', 'Interview Score']; data1 = [0.30, 0.15, 0.35, 0.20]; // Weights data2 = [5, 0.9, 75, 92]; // Example Values (Education normalized) } else if (currentApplicationType === 'grant') { labels = ['Impact Score', 'Applicant Experience', 'Funding Need', 'Alignment Score']; data1 = [0.35, 0.20, 0.15, 0.30]; // Weights data2 = [8, 10, 50000, 9]; // Example Values } chartInstance = new Chart(ctx, { type: 'bar', data: { labels: labels, datasets: [{ label: 'Factor Weight (%)', data: data1.map(function(w) { return w * 100; }), backgroundColor: 'rgba(0, 74, 153, 0.6)', borderColor: 'rgba(0, 74, 153, 1)', borderWidth: 1 }, { label: 'Example Value', data: data2, backgroundColor: 'rgba(100, 150, 200, 0.6)', borderColor: 'rgba(100, 150, 200, 1)', borderWidth: 1 }] }, options: { responsive: true, maintainAspectRatio: false, scales: { y: { beginAtZero: true, ticks: { callback: function(value) { if (currentApplicationType === 'loan' || currentApplicationType === 'creditCard' || currentApplicationType === 'grant') { if (labels[this.index] === 'Debt-to-Income Ratio' || labels[this.index] === 'Credit Utilization' || labels[this.index] === 'Funding Need') return value + '%'; if (labels[this.index] === 'Income' || labels[this.index] === 'Loan Amount') return '$' + value.toLocaleString(); if (labels[this.index] === 'Credit Score' || labels[this.index] === 'Credit History' || labels[this.index] === 'Experience' || labels[this.index] === 'Interview Score') return value; if (labels[this.index] === 'Impact Score' || labels[this.index] === 'Alignment Score') return value; } else if (currentApplicationType === 'job') { if (labels[this.index] === 'Skills Match') return value + '%'; if (labels[this.index] === 'Experience' || labels[this.index] === 'Interview Score') return value; if (labels[this.index] === 'Education') return value; // Normalized } return value; } } }, y1: { // Secondary Y-axis for weights if needed, or just use labels type: 'linear', position: 'right', grid: { drawOnChartArea: false, }, ticks: { callback: function(value) { if (labels[this.index] === 'Factor Weight (%)') return value + '%'; return value; } } } }, plugins: { legend: { position: 'top', }, title: { display: true, text: 'Key Factors and Their Influence' } } } }); } // Add Chart.js library dynamically if not present (function() { var script = document.createElement('script'); script.src = 'https://cdn.jsdelivr.net/npm/chart.js@3.7.0/dist/chart.min.js'; script.onload = function() { // Initialize calculator and chart after Chart.js is loaded updateCalculatorLogic(); updateChart(); }; document.head.appendChild(script); })(); // FAQ Toggle document.addEventListener('DOMContentLoaded', function() { var faqQuestions = document.querySelectorAll('.faq-question'); faqQuestions.forEach(function(question) { question.addEventListener('click', function() { var answer = this.nextElementSibling; answer.classList.toggle('visible'); }); }); });

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