ICAP PRC-2 Quantitative Analysis for Business study plan

Compute ratios, percentages, proportions, and averages for business scenarios (markup, margin, break-even) without a calculator where possible.

Solve problems involving simple and compound interest, depreciation, and basic annuity formulas using the relevant equations.

Construct and interpret frequency distributions, histograms, and ogives from raw data sets.

Calculate mean, median, mode, quartiles, and standard deviation for grouped and ungrouped data, and explain what each measure indicates.

Distinguish between measures of central tendency and dispersion, and select the appropriate measure for a given business context.

Apply the multiplication and addition rules of probability to solve problems involving independent and dependent events.

Compute conditional probabilities and apply Bayes' theorem to business decision scenarios.

Calculate expected value and variance for discrete random variables, and interpret the results in context.

Identify and apply the binomial, Poisson, and normal distributions to appropriate business problems.

Use standard normal tables to find probabilities and z-scores, and relate them to quality control and risk assessment.

Compute covariance and correlation coefficients (Pearson and Spearman) from raw data and interpret the strength and direction of relationships.

Construct scatter diagrams and identify linear and non-linear patterns.

Fit a simple linear regression line using least squares and interpret the slope and intercept in business terms.

Calculate and interpret the coefficient of determination (R²) and standard error of the estimate.

Use regression equations to make predictions and discuss the limitations of extrapolation.

Construct Laspeyres, Paasche, and Fisher price and quantity indices from given data and explain their differences.

Interpret index numbers, including base shifting, deflating, and splicing, and discuss common biases.

Decompose a time series into trend, seasonal, cyclical, and irregular components using moving averages.

Calculate seasonal indices using the ratio-to-moving-average method and apply them to deseasonalize data.

Forecast future values using trend projection and exponential smoothing, and evaluate forecast accuracy with MAD or MSE.

Apply the time value of money concepts to calculate present and future values of single sums, annuities, and perpetuities.

Compute net present value (NPV), internal rate of return (IRR), and payback period for investment projects.

Evaluate capital budgeting decisions using NPV, IRR, and profitability index, and explain the superiority of NPV.

Calculate loan amortization schedules and the effective annual rate (EAR) for given nominal rates and compounding frequencies.

Use discounted cash flow techniques to value bonds and simple financial assets.

Construct a decision tree for a business problem with sequential decisions and uncertain outcomes.

Apply the maximax, maximin, and minimax regret criteria to a payoff table and interpret the results.

Calculate expected monetary value (EMV) and expected opportunity loss (EOL) for decision alternatives.

Determine the value of perfect information (EVPI) and explain its use in decision-making.

Perform sensitivity analysis on probabilities and payoffs to identify robust decisions.

Formulate linear programming problems from word problems, identifying decision variables, objective function, and constraints.

Solve two-variable LP problems graphically, including identifying feasible region, corner points, and optimal solution.

Interpret shadow prices and slack variables in the context of resource allocation.

Explain the central limit theorem and its role in sampling distributions.

Construct confidence intervals for means and proportions, and determine sample size for a desired margin of error.

Set up null and alternative hypotheses for business scenarios and choose the appropriate test (z-test, t-test, proportion test).

Perform hypothesis tests for means and proportions, interpret p-values, and distinguish Type I and Type II errors.

Review decision theory, LP, and sampling concepts by solving mixed exam-style questions under timed conditions.

Identify personal weak areas from practice tests and create a targeted revision checklist.

Simulate a full exam with a time limit, focusing on accuracy and time management.