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CA Foundation Statistics (Paper 3C) Full Course By Prof. Hemal Daftary

2,999.00

📈 CA Foundation Statistics (Paper 3C) Full Course — By Prof. Hemal Daftary

🎯 Target Attempts: May 2026 & September 2026 Exams (100% ICAI Aligned).
⏱️ Course Duration & Lectures: 267 On-Demand Micro-Lectures (~43 Hours 13 Minutes).
📊 Views & Validity: 3 Times Views with 12 Months Validity.
🗣️ Video Language: Hindi + English.
📥 Digital Resources: 1 Downloadable Resource included.
⚡ Effective Pricing: High-yield analytical training at just ₹69.74 / Hour.

🌟 Learning Pedagogy & Exam Strategy
• 💡 Analytical Foundations: Conceptual mastery of statistical principles, data interpretation, and business decision-making.
• 📊 Micro-Lecture Learning: 267 bite-sized topic modules engineered for fast concept retention and rapid formula recall.
• ✍️ Step-by-Step Problem Solving: Comprehensive practical problem sets solved with shortcuts and calculation techniques.
• 🎯 100% Exam-Oriented Focus: In-depth coverage of probability distributions, theoretical models, and index numbers.

📋 Comprehensive Syllabus & Chapter Breakdown (267 Lectures)

Part A: Descriptive Statistics & Sampling
• Introduction to Statistics (1 Lecture)
• Statistical Description of Data (14 Lectures)
• Sampling (17 Lectures)
• Measures of Central Tendency (29 Lectures)
• Measures of Dispersion (23 Lectures)
• Correlation Analysis (26 Lectures)
• Regression Analysis (20 Lectures)

Part B: Probability & Distributions
• Index Numbers (35 Lectures)
• Probability (31 Lectures)
• Random Variables (19 Lectures)
• Binomial Distribution (20 Lectures)
• Poisson Distribution (13 Lectures)
• Normal Distribution (19 Lectures)

👨‍🏫 About the Faculty — Prof. Hemal Daftary

Statistics Mentor

Subject Domain
Business Statistics & Quantitative Methods for CA Foundation aspirants.
Teaching Pedagogy
Clear, straightforward explanations with practical application, breaking complex distributions into intuitive concepts.
ICAI Alignment
100% mapped with ICAI question patterns, historical testing trends, and chapter-wise objective problems.