All Papers
FoundationsEntirely New Paper
F3 — Decision Making with Data
F3 Decision Making with Data is an entirely new paper with no direct ACCA predecessor. It introduces data literacy, basic analytics, and data-informed decision making at the entry level. Students learn to interpret data presentations, understand basic statistical concepts, use spreadsheets for analysis, and apply data to business decisions.
FormatCBE · 2 hours · 100 marks
Pass Mark50%
Legacy PaperNone — entirely new paper
Sections6 sections (A, B, C, D, E, F)
Current-syllabus equivalentOur paper mapping does not identify a current ACCA paper for F3.
Transition Planner Exam Format
Section A: 45 × 2-mark OTs (90 marks) · Section B: 1 × 10-mark MTQ · 2 hours · 100 marks
Key Changes vs Legacy Paper
- Entirely new paper — no direct ACCA predecessor
- Introduces data literacy and analytics at entry level
- Covers spreadsheet skills, basic statistics, data visualisation
- Includes data ethics and decision-making frameworks
Syllabus Comparison — F3
| Change | Area / Topic | Detail |
|---|---|---|
| ORIGIN | A1 Sampling methods | MA/FMA B1 — identical content (sampling methods). MA/FMA B3 covered data types (categorical/numerical) which is now in F3 A1. |
| ORIGIN | A2 Summarising and analysing data | MA/FMA B3 (partial) — mean/mode/median and dispersion measures for ungrouped data retained. Removed from F3: mean for grouped data; expected values; descriptive vs inferential analysis; normal distribution properties and graph interpretation. |
| ORIGIN | A3 Linear functions (including high-low method) | MA/FMA B2a (structure of linear functions), B2b (high-low method), B2d (scatter diagrams). MA/FMA B2b also covered advantages/disadvantages of high-low — retained in F3 A3d. |
| ORIGIN | A4 Linear regression | MA/FMA B2e (correlation, coefficient of determination, regression analysis), B2f (use regression for forecasts), B2h (advantages/disadvantages of linear regression). Note: MA/FMA B2g (adjust historical/forecast data for price movements) is not in F3 A4. |
| ORIGIN | A5 Time series analysis | MA/FMA B2i–B2m — all time series content retained: components, moving averages, trend calculation, additive and multiplicative forecasting, advantages/disadvantages. MA/FMA B2n–B2p (index numbers — Laspeyre/Paasche; product life cycle) are NOT in F3. |
| ORIGIN | A6 Big data | MA/FMA B3a–B3c — 5Vs, three types, main uses. MA/FMA B3d–B3j (data types, descriptive/inferential, mean/median, variance, expected values, normal distribution) are split: B3a–c go to F3 A6; B3d–j go partly to F3 A2 (measures of dispersion) and the rest are removed. |
| ORIGIN | B1 Relevant costing principles | NEW at Foundations level. Previously only in PM (Applied Skills — F5). Simplified: asset replacement decisions and opportunity cost excluded from F3 scope. Appears also in K2 Section E1a at Knowledge level. |
| ORIGIN | B2 Limiting factor analysis | NEW at Foundations level. Previously only in PM (Applied Skills — F5). Single resource constraint only (no linear programming/multiple constraints). Appears also in K2 Section E1b at Knowledge level (K2 adds shadow price concept). |
| ORIGIN | B3 CVP analysis | NEW at Foundations level. Previously only in PM (Applied Skills — F5). Appears also in K2 Section E1c at Knowledge level (K2 adds multi-product CVP and P/V chart preparation). F3 restricts to single product; K2 adds multi-product. |
| ORIGIN | B4 Inventory management techniques | MA/FMA C1a (partial) — ordering/holding costs, EOQ, reorder levels retained. NOT in F3: LIFO valuation; gradual replenishment EOQ; buffer inventory calculations; interpret material inventory account entries. Adds material input requirements with wastage allowance as a new explicit outcome. |
| ORIGIN | C1 Compounding and discounting | MA/FMA D4d (simple vs compound interest; nominal vs effective interest rates) and D4e (compounding and discounting). Retained fully in F3 C1. |
| ORIGIN | C2 Investment appraisal techniques | MA/FMA D4f–D4k (cash flow vs profit; NPV and IRR; annuity and perpetuity; calculate NPV/IRR/payback; interpret results). F3 adds ROCE explicitly as a named method. Annuities and perpetuities are NOT in F3 C2 (they are in K2 Section E2 at Knowledge level). MA/FMA D4a–D4c (importance of investment planning; asset vs expense; steps in asset expenditure budget) are also not in F3. |
Syllabus Breakdown
A
Data and Information in Business
A1
The role of data and information
- Distinguish between data, information and knowledge
- Identify sources of data: internal and external, primary and secondary
- Understand the value of data as an organisational asset
- Identify the characteristics of useful information: accurate, complete, timely, relevant, understandable
B
Data Collection and Organisation
B1
Data types and collection
- Identify data types: qualitative, quantitative, discrete, continuous
- Understand sampling methods: random, systematic, stratified, cluster, quota
- Understand the importance of data quality and data cleansing
B2
Data organisation
- Organise data using tables, databases and spreadsheets
- Sort, filter and group data
- Understand data structures: flat files, relational databases
C
Spreadsheet Skills for Analysis
C1
Spreadsheet functions
- Use key spreadsheet functions: SUM, AVERAGE, COUNT, MAX, MIN, IF, VLOOKUP
- Create and format charts and graphs
- Use pivot tables for data summarisation
- Apply conditional formatting
D
Statistical Concepts and Data Analysis
D1
Descriptive statistics
- Calculate and interpret measures of central tendency: mean, median, mode
- Calculate and interpret measures of dispersion: range, variance, standard deviation
- Understand frequency distributions and histograms
D2
Correlation and trends
- Understand correlation: positive, negative, no correlation
- Interpret scatter diagrams and correlation coefficients
- Identify trends in time series data
- Calculate moving averages
D3
Index numbers and probability
- Calculate and interpret simple index numbers
- Understand basic probability concepts
- Apply expected values to decision making
E
Presenting and Interpreting Data
E1
Data visualisation
- Select appropriate charts: bar, line, pie, scatter, histograms
- Interpret charts and graphs
- Identify misleading data presentations
- Present data clearly and accurately
E2
Report writing
- Structure a short data-based report
- Draw conclusions from data analysis
- Make recommendations based on data
F
Data-Informed Decision Making
F1
Decision making frameworks
- Apply break-even analysis
- Understand cost-volume-profit (CVP) relationships
- Apply relevant costing principles to short-term decisions
- Use expected values in decision making under uncertainty
F2
Data ethics and limitations
- Understand data protection and privacy principles
- Recognise limitations of data in decision making
- Understand bias in data collection and analysis