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Syllabus ReferenceGridHoursWeightage
ABasic Mathematics12-1510-20
BFinancial Mathematics15-1815-25
CData Analysis18-2420-30
DProbability and Probability Distribution10-1515-20
ESampling and Decision making15-1820-25

PRC-2 QUANTITATIVE METHODS Key Examinable Technical Competencies

Syllabus Ref.Learning OutcomesProficiency LevelTesting Level
A. Basic Mathematics
1Solve two-variable simultaneous equations and quadratic equations.P1T1
2Prepare graphs of linear equation.P1T1
  3Apply arithmetic and geometric progression in business problems to calculate monthly instalments, first instalment, total amount paid and total time required for settlement of a loan etc.  P1  T1
4Formulate a system of linear programming for a business problem.P1T1
  5Identify constraints, feasible region, cost minimization or profit maximization functions, no feasible solution using linear programming.  P1  T1
6Prepare a graphical solution of a linear programming problem.P1T1
B. Financial Mathematics  
1Apply simple and compound interest rate on single or series of amounts to find out interest amount and future values.P1T1
2Apply discount rate on single or series of amounts including perpetuity to find out present values.P1T1
3Calculate the net present value (NPV) of future cash flows.P1T1
4Calculate internal rate of return on a project.P1T1
Syllabus Ref.Learning OutcomesProficiency LevelTesting Level
C. Data Analysis  
1Classify different types of data.P1T1
2Explain data collection through various methods.P1T1
3Summarize and present data.P1T1
4Calculate various measures of central tendency.P1T1
5Identify the characteristics and measures of dispersion.P1T1
6Compute the degree of variation or variability in a distribution.P1T1
7Discuss the index number and its types.P1T1
8Calculate index number and discuss the practical application of index no.P1T1
9Construct deflated or inflated series using index numbers.P1T1
10Explain scatter diagrams their construction, uses and limitations.P1T1
11Explain the concept of regression lines and their uses and limitations.P1T1
12Calculate a linear regression line (line of best fit) using least squares.P1T1
13Calculate and discuss correlation coefficients, rank correlation coefficients and determination.P1T1
D. Probability and Probability Distribution  
1Calculate the total number of possible outcomes and selections from a set of data using counting techniques.P1T1
2Discuss and compute probability using different techniques.P1T1
3Discuss and estimate the probability distribution using different techniques.P1T1
E. Sampling and Decision making  
1Explain the term population, sample, sample distribution and sampling distribution.P1T1
2Explain methods for selecting a sample.P1T1
3Explain a sampling distribution of the sample means.P1T1
4Calculate the mean and standard error of a sampling distribution of sample and proportion means.P1T1
5Apply hypothesis test of proportions and difference between proportions.P1T1
6Apply hypothesis test of population means based on small and large samples.P1T1
Syllabus Ref.Learning OutcomesProficiency LevelTesting Level
7Apply hypothesis tests of the difference between two population means.P1T1
8Apply the Chi-square distribution to perform tests of goodness of fit and independence.P1T1

PRC-2 QUANTITATIVE METHODS Key Examinable Professional Skills

1Evaluate given information through integration and analysis.
2Apply critical thinking skills to solve problems.
3Apply intellectual agility.

PRC-2 QUANTITATIVE METHODS Key Examinable Professional Values, Ethics and Attitude

1Apply an inquiring mind when collecting and assessing data and information
2Use critical thinking in determining appropriate course of action.

Specific Examinable Knowledge Reference

1Array, Frequency distribution, Tally, Class boundaries
2Bar and pie chart
3Histograms, frequency polygons, Ogives, graphs, stem and leaf displays, Box and whisker plots
4Mode, median, arithmetic, geometric and harmonic means
5Standard deviation
7Laspeyre, Paasche and Fisher index
8Scatter diagrams
9mn counting rule and factorials
10Permutations and combination
11Addition and multiplication law for probability
12Conditional and complementary probabilities
13Binomial, Hyper-Geometric, Poisson, Normal distribution
14Normal approximation
15Random, systematic, stratified, multi-stage, cluster and quota sampling


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