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.

GRID | Weightage |

Business Mathematics | |

Basic Mathematics | 10 – 15 |

Mathematics of Finance | 15 – 20 |

Calculus and Linear Programming | 15 – 20 |

Statistical Data analysis for Decision making | |

Statistical Concepts | 10 – 15 |

Correlation & Regression Analysis | 10 – 15 |

Probability and probability distribution | 10 – 15 |

Sampling and decision making | 10 – 15 |

Total | 100 |

## Detailed Syllabus Contents:

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

BUSINESS MATHEMATICS

Basic Mathematics

- Exponential and logarithmic functions
- Equation of straight line
- Simultaneous linear equations and their application
- Solving Quadratic Equation
- 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

Focus:

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