# Syllabus of PIPFA Level 1 Quantitative Methods

Get access to latest and updated syllabus of PIPFA Level 1 Quantitative Methods now. Here you will find detailed course content or Syllabus of PIPFA Leve1 Quantitative Methods for upcoming attempt.

Unfortunately, PIPFA does not publish it’s own study text. But you need not to worry as you can use study texts of ICAP and/or ICMAP. You will have the advantage on other students. The reason being ICAP and ICMAP study texts are comparatively more difficult than the books recommended by PIPFA examination body.

## Syllabus GRID:

Here is the grid for syllabus of PIPFA Leve 1 Quantitative Methods.

## Detailed Syllabus Contents:

The detailed Syllabus of PIPFA Level 1 Quantitative Methods for upcoming attempt is given below.

Basic Mathematics

• Exponential and logarithmic functions
• Equation of straight line
• Simultaneous linear equations and their application
• Factorization of Equation
• (Square of sum of two expressions, Square of difference of two expressions, Difference between two squares Completion of squares)”
• Co-ordinate System (Understanding of slope, intercept, slope intercept form of equation and preparation of graph of linear equations)
• Arithmetic and Geometric progression and their application.

Mathematics of Finance

• Simple and Compound Interest
• Annual, periodic and effective interest rates
• Time value of money
• Present Value and Discounting
• Future Values
• Net Present Value
• Annuities and Perpetuities
• Internal rate of return (including the use of interpolation)

Calculus

• Rules for finding derivatives (Sum, difference, product and quotient rule)
• Marginal Revenue, Cost and Profit functions
• Maximization and minimizing problems and the use of second order derivatives

Linear Programming

• Linear inequalities
• Converting simple situations into linear inequalities
• Graphical solution to linear programming problems
• Feasible region (bounded as well as unbounded), redundant constraints, no feasible solution, alternative optimum solution

STATISTICAL DATA ANALYSIS FOR DECISION MAKING

Statistical Concepts

• Collection and tabulation of data
• Bar charts, pie charts, histograms, frequency polygons, ogives, stem and leaf display
• Measures of central tendencies (Arithmetic/geometric/harmonic means, median, mode)
• Measures of dispersion (standard deviation, variance)
• Index numbers, weighted index numbers (Laspeyre, Paasche and Fisher price indices), purchasing power and deflation of income

Correlation & Regression Analysis

• Scatter diagram
• Linear regression lines by method of least squares
• Co-efficient of correlation and determination
• Rank correlation
• Interpretation

Probability and Probability Distribution

• Permutations and Combinations
• Probability
• Addition law for mutually exclusive and not mutually exclusive events
• Multiplicative laws for dependent and independent events
• Probability Distributions (Binomial, Hyper-geometric and Normal)

Sampling and Decision Making

• Population and sample
• Random Sampling
• Sampling with and without replacement
• Sampling Distribution and Sampling Error of mean
• Hypothesis testing (population mean, population proportion, difference between population means and difference between two population proportions)
• Estimation (Confidence intervals for population mean, proportion and variance and difference between population mean, proportion and variance.
• Chi-Square distribution (test of independence and test of goodness of fit) indices), purchasing power and deflation of income

## Learning outcomes:

On the successful completion of this course students should be able to;

• Understand basic mathematical tools that would be used in financial analysis at the next levels
• Apply financial mathematics to solve problems related to financial management
• Use calculus to solve maximization and minimization problems
• Solve problems involving linear programming by the use of graphical methods
• Understand different methods of collecting and presenting statistical data
• Compute and analysis measures of central tendency and measures of dispersion
• Understand the concept of index numbers and their practical applications
• Using regression and correlation analysis to study historic trends and predicting changes independent variable on the basis of its relationship with independent variable
• Compute probability involving discreet as well as continuous data
• Making decisions using sampling techniques involved in hypothesis testing, confidence interval estimation and determination of probability

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syllabus of PIPFA Level 1 Quantitative Methods syllabus of PIPFA Level 1 Quantitative Methods syllabus of PIPFA Level 1 Quantitative Methods syllabus of PIPFA Level 1 Quantitative Methods syllabus of PIPFA Level 1 Quantitative Methods