Exam format and priority
The syllabus states CCA 30 marks and ESE 70 marks in a 2-hour written exam: five of eight 2-mark questions from the last two units (Modules 3 and 4); four of six 5-mark short essays; and two of four 20-mark essays (problems and case studies). Do not assume an individual question is guaranteed.
Descriptive measures and interpretation, correlation/regression, probability rules, logic aptitude topics, and both Excel assignments.
Data classification and graphs, covariance, ranks, model characteristics and business applications.
Definitions, formulas, theory-only concepts and clear distinctions.
First learn summaries and formula meanings; then practise relationship/probability problems; then do logic sets and complete the applied Excel work.
Revision checklist
10 core ideas: classification; tabulation; frequency distribution; graph choice; AM; weighted AM; median/mode; dispersion; skewness; kurtosis.
Key terms: class interval, frequency, weighted mean, quartile, mean deviation, SD, CV, skew, tail, histogram.
Formula prompts: AM=Σx/n; weighted AM=Σwx/Σw; range=max−min; QD=(Q₃−Q₁)/2; MD=Σ|x−A|/n; CV=(SD/mean)×100%.
Common traps: unsorted median; weights not applied; CV used for zero mean; skewness/kurtosis coefficient convention left unstated.
Revision checklist
10 core ideas: paired data; scatter; covariance; correlation direction; correlation strength; Pearson r; Spearman ranks; probable error theory; regression; prediction.
Key terms: association, covariance, rank, coefficient, regression line, slope, x-on-y, y-on-x, probable error, extrapolation.
Formula prompts: Pearson coefficient; untied Spearman formula; regression lines through (x̄,ȳ). Probable error is theory only in this syllabus.
Common traps: correlation is not causation; Pearson measures linear association; tie handling for Spearman; select regression direction according to what is being predicted.
Revision checklist
10 core ideas: experiment; outcome; sample space; event; equally likely outcomes; classical probability; complement; addition rule; multiplication rule; binomial/Poisson/normal model characteristics.
Key terms: favourable outcome, mutually exclusive, intersection, union, independent, conditional, count, rate, distribution, uncertainty.
Formula prompts: P(A)=favourable/total under equally likely outcomes; addition rule subtracts overlap; multiplication rule uses conditional probability; independent product rule. Named distributions are theory only.
Common traps: double-count overlap; assume independence; use classical definition when outcomes are not equally likely; treat theory-only distributions as required numerical syllabus.
Revision checklist
10 core ideas: number series; alternating patterns; coding-decoding; odd one out; direction sense; linear seating; circular seating; blood relations; AP/GP; inductive/deductive reasoning.
Key terms: sequence, rule, code, orientation, displacement, constraint, common difference, common ratio, induction, deduction.
Formula prompts: AP aₙ=a₁+(n−1)d; GP aₙ=a₁rⁿ⁻¹.
Common traps: assume a sequence rule before checking every term; confuse facing direction with destination; switch perspective in seating puzzles; mistake an observed pattern for deductive proof.
Expected / Exam-Focused question bank
Questions below are derived from the syllabus. The ESE specifies that 2-mark questions come from the last two units (Probability and Logic).
2-mark practice (Modules 3 and 4 focus)
- State the classical definition of probability.
- Write the addition rule for two events.
- When are two events independent?
- What does the binomial distribution model?
- Define an arithmetic progression and common difference.
- Distinguish inductive and deductive reasoning.
- What is meant by displacement in a direction problem?
- What does a circular seating arrangement require you to keep consistent?
5-mark short-essay practice
- Calculate and interpret mean, median and mode for a small business data set.
- Explain range, QD, mean deviation, SD and CV.
- Explain Pearson correlation and interpret its direction and magnitude.
- Compare correlation and regression, including x-on-y and y-on-x.
- Explain probability addition and multiplication rules with examples.
- Describe the characteristics of binomial, Poisson and normal distributions (theory).
- Solve a direction/seating/blood-relation reasoning problem and show the diagram.
- Explain skewness and kurtosis and describe how to examine them with a histogram.
20-mark essay/case-study practice
- Analyse a supplied sales data set using suitable centre and dispersion measures; interpret the business implications.
- Given paired expenditure and income data, examine correlation and regression; explain limits of prediction.
- Prepare a business-data case analysis from classification and tabulation through summary, relationship and conclusion.
- Explain probability rules and the syllabus distributions in a business uncertainty scenario.
- Complete a logic case involving number patterns, arrangements or directions, with systematic working.
- Describe how to conduct and report the Excel assignment on real-world data.
Model answer structure
2 marks: accurate definition/rule plus a short example or distinction.
5 marks: explain the concept, give the formula or steps, show a compact example and interpret.
20 marks: introduce the business question; organise data; select and justify techniques; show calculations/tables; explain results; state limitations; conclude with evidence-based implications.
Assignment completion checklist
7-day revision plan
| Day | Focus and output |
|---|---|
| 1 | Tables/graphs, central tendency and weighted mean; solve raw-data examples. |
| 2 | Dispersion, CV, skewness and kurtosis; analyse one histogram. |
| 3 | Covariance, scatter, Pearson/Spearman and correlation interpretation. |
| 4 | Regression lines, coefficients, probability rules and distribution theory. |
| 5 | Logic: sequences, coding, odd one out and progressions. |
| 6 | Direction, seating, blood relations, induction/deduction; complete assignment checks. |
| 7 | Timed ESE practice in 2/5/20 mark formats; review errors and conclusions. |
14-day revision plan
| Day | Focus |
|---|---|
| 1 | Classification, tabulation and frequency distributions |
| 2 | Diagrams, graphs and interpretation |
| 3 | AM, weighted AM, median and mode |
| 4 | Range, QD, MD, SD and CV |
| 5 | Skewness, kurtosis and histogram/normal overlay assignment |
| 6 | Covariance and scatter diagrams |
| 7 | Pearson and Spearman correlation; probable error theory |
| 8 | Regression equations, coefficients and interpretation |
| 9 | Classical probability and event language |
| 10 | Addition/multiplication rules; distribution characteristics |
| 11 | Number series, coding and odd one out |
| 12 | Directions, linear/circular seating and blood relations |
| 13 | AP/GP and inductive/deductive reasoning; finish Excel analysis |
| 14 | Mixed timed practice, essay structure and correction |
Final 24-hour checklist
If you can do these things, you are exam ready: choose an appropriate method, show clear working, interpret a result in business context and explain the limitations.