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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

ChangeArea / TopicDetail
ORIGINA1 Sampling methodsMA/FMA B1 — identical content (sampling methods). MA/FMA B3 covered data types (categorical/numerical) which is now in F3 A1.
ORIGINA2 Summarising and analysing dataMA/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.
ORIGINA3 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.
ORIGINA4 Linear regressionMA/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.
ORIGINA5 Time series analysisMA/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.
ORIGINA6 Big dataMA/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.
ORIGINB1 Relevant costing principlesNEW 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.
ORIGINB2 Limiting factor analysisNEW 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).
ORIGINB3 CVP analysisNEW 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.
ORIGINB4 Inventory management techniquesMA/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.
ORIGINC1 Compounding and discountingMA/FMA D4d (simple vs compound interest; nominal vs effective interest rates) and D4e (compounding and discounting). Retained fully in F3 C1.
ORIGINC2 Investment appraisal techniquesMA/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
Prev: F2 — Management Information and CostingNext: K1 — Financial Accounting