PRC-2 Quantitative Methods by Sir Naeem Ullah
This course is part of the PRC Module
Students already enrolled: 10,000+
Naeem Ullah
Instructor
Fee: Rs 10,000
What you will Learn
The Quantitative Methods course is designed to provide students with a strong foundation in quantitative techniques and tools that are essential for financial and business analysis.
Course Content
Basic Mathematics:
a. Solve simultaneous equations and quadratic equations.
b. Graph linear equations.
c. Apply arithmetic and geometric progressions in business calculations.
d. Formulate and solve linear programming problems.
e. Financial Mathematics:
Calculate simple and compound interest.
a. Determine present and future values using discount rates.
b. Compute net present value (NPV) and internal rate of return (IRR) for cash flows.
3.Data Analysis:
a. Classify data types and collect data through various methods.
b. Summarize and present data, calculate measures of central tendency and dispersion.
c. Understand index numbers, construct them, and apply them practically.
d. Use scatter diagrams, regression lines, and correlation coefficients for data analysis.
Probability and Probability Distribution:
a. Calculate outcomes and probabilities using counting techniques.
b. Estimate probability distributions using various methods.
5. Sampling and Decision Making:
Understand population, sample, and sampling distribution.
b. Explain methods for sample selection and sampling distribution of sample means.
c. Perform hypothesis tests for proportions, population means, and differences.
d. Apply Chi-square distribution for tests of goodness of fit and independence.
Additional Content
1. Data Representation:
a. Use arrays, frequency distributions, and tally charts to organize data.
b. Create bar and pie charts for visual representation.
c. Utilize various statistical graphs and plots like histograms, frequency polygons, ogives, stem and leaf displays, and box and whisker plots.
2. Statistical Measures:
a. Calculate measures of central tendency such as mode, median, and means (arithmetic, geometric, and harmonic).
b. Compute standard deviation and variance.
c.Apply different index numbers like Laspeyre, Paasche, and Fisher indices.
3. Probability and Distributions:
a. Understand probability concepts including permutations, combinations, and addition/multiplication laws.
b. Explore conditional and complementary probabilities.
c. Work with probability distributions, including binomial, hypergeometric, Poisson, and normal distributions, along with normal approximations.
4. Sampling:
a. Apply various sampling methods, including random, systematic, stratified, multi-stage, cluster, and quota sampling.
