ECON1012 · Data Analytics
The Complete Exam Bible · S2 2026Data Analytics
ECON 1012 Data Analytics is Adelaide University's first-year introduction to statistics for business and economics — a School of Economics course with no prerequisites. Ten weekly modules on myLearning build through three arcs: describing data (Weeks 1–3), statistical inference (Weeks 4–7) and correlation and regression (Weeks 8–10), moving from means, histograms and probability to confidence intervals, hypothesis tests and simple linear regression, with Excel skills built in workshops along the way.
Assessment is a Descriptive Statistics Case Study (10%), a Statistical Inference Assignment (20%), a Data Analysis Case Study (20%) and a final exam worth 50% — 25 multiple-choice questions plus 3 case-study questions in 180 minutes, covering Weeks 1–10. There are no hurdles: an overall 50% passes. And the exam is winnable by design — you bring one double-sided A4 note sheet, Z and t tables are provided, the MCQs are styled like the module practice quizzes, and the case-study questions follow the format rehearsed in workshops every week.
What ECON 1012 covers
Ten weekly modules → one exam-ready map: descriptive statistics, probability, inference, and regression — exactly as ECON 1012 teaches them.
How ECON 1012 is assessed
| Component | Weight | Format |
|---|---|---|
| Descriptive Statistics Case Study | 10% | Case study applying the course's descriptive-statistics tools · due date published on myLearning |
| Statistical Inference Assignment | 20% | Assignment on the statistical-inference topics · due date published on myLearning |
| Data Analysis Case Study | 20% | Case study applying the course's data-analysis tools · due date published on myLearning |
| Final Exam | 50% | 25 multiple-choice questions + 3 case-study questions · 180 minutes · invigilated · one double-sided A4 note sheet permitted · non-wireless calculators allowed · Z and t tables provided · covers Weeks 1–10 |
95% confidence interval for a mean (note-sheet + t-table style)
- 1 markChoose the right interval. The population standard deviation σ is unknown (we only have s), so use the Student t interval x̄ ± t·(s/√n) with df = n − 1 = 24.
- 1 markCompute the standard error: s/√n = 4.50/√25 = 4.50/5 = 0.90.
- 1 markFind the critical value. 95% confidence means α = 0.05, so α/2 = 0.025; the t table gives t₀.₀₂₅,₂₄ = 2.064.
- 2 marksCompute the margin of error: 2.064 × 0.90 = 1.8576 ≈ 1.86.
- 1 markBuild the interval: 18.40 − 1.8576 = 16.5424 and 18.40 + 1.8576 = 20.2576, so the 95% CI is ($16.54, $20.26).
- 2 marksInterpret in business language: we are 95% confident that the mean weekday spend across all customers lies between $16.54 and $20.26 — if we repeatedly drew samples of 25 and built intervals this way, about 95% of those intervals would capture the true mean μ.
Key terms
- Parameter vs statistic
- A parameter is a descriptive measure of a population (Greek letters: μ, σ, ρ); a statistic is the matching measure computed from a sample (x̄, s, r). The whole inference arc of ECON 1012 is about using statistics you can calculate to learn about parameters you cannot observe.
- Descriptive vs inferential statistics
- Descriptive statistics organises, summarises and presents data (tables, charts, means, standard deviations); inferential statistics draws conclusions about a population from sample data. The course moves from the first arc to the second, then applies both to relationships between variables.
- Standard error (SE)
- The standard deviation of a sample statistic across repeated samples. For a sample mean it is σ/√n (or s/√n when σ is unknown); it shrinks as n grows, which is why larger samples give tighter confidence intervals and more decisive tests.
- Central Limit Theorem (CLT)
- If a random sample is drawn from any population, the sampling distribution of the sample mean x̄ is approximately normal for a sufficiently large sample size (usually n ≥ 30). This result is what licenses the Z and t procedures used through the inference weeks.
- Confidence interval
- An interval estimate of the form point estimate ± critical value × standard error. '95% confident' describes the long-run procedure, not one interval: across repeated samples, about 95% of intervals built this way capture the true parameter.
- p-value
- The evidence against the null hypothesis — the smaller the p-value, the stronger the evidence. Decision rule: if the p-value is below α, reject H₀. The course reads p below 0.01 as overwhelming evidence and p above 0.10 as no evidence.
- Type I and Type II error
- A Type I error rejects a true H₀ (probability α, the significance level); a Type II error fails to reject a false H₀ (probability β). The two probabilities are inversely related — pushing one down pushes the other up, all else equal.
- Coefficient of determination (R²)
- In regression, the proportion of the variation in Y explained by variation in X: R² = SSR/SST, ranging from 0 to 1, and equal to the square of the correlation coefficient r. An R² of 0.64 means 64% of the variation in Y is explained by the model.
ECON 1012 FAQ
Is ECON 1012 hard?
It is a cumulative skills course rather than a memorisation course: the hypothesis tests of Week 7 reuse the sampling distributions of Week 5, which reuse the normal-table technique of Week 4, so falling behind is the main risk — and the final exam carries 50% of the grade. Structurally, though, it is set up to be winnable: there are no hurdle requirements, you bring one double-sided A4 note sheet into the exam, Z and t tables are provided, the MCQs are styled like the module practice quizzes (re-attemptable with randomised questions), and the case-study questions follow the format you rehearse in workshops all semester.
Does ECON 1012 have a final exam?
Yes. The final exam is worth 50% and consists of 25 multiple-choice questions plus 3 case-study questions in 180 minutes, covering Weeks 1–10. It is invigilated; you may bring one double-sided A4 note sheet and a non-wireless calculator, and Z and t tables are provided with the paper.
Is ECON 1012 offered in Semester 2 2026?
Yes. The official S2-2026 course outline confirms ECON 1012 Data Analytics runs in Semester 2 2026, starting 4 August 2026, delivered on campus. The course is also offered in Semester 1, so you can take it in either half of the year — always confirm delivery details on the current course outline before enrolling.
Is the final exam a hurdle?
No. The official outline lists no hurdle requirements on any component. You pass ECON 1012 on an overall mark of at least 50% across the four assessments, so a weaker exam can be offset by strong case-study and assignment marks — although at 50% weight the final still shapes your grade more than anything else.
Can I bring notes into the ECON 1012 exam?
Yes — one double-sided A4 note sheet, prepared however you like. Combined with the Z and t tables provided in the exam room and a permitted non-wireless calculator, this means the exam rewards choosing the right procedure and interpreting the result, not memorising formulas. Building the sheet yourself is one of the best revision exercises in the course.
What software does ECON 1012 use — do I need to code?
Excel is the course's software, taught hands-on in workshops (histograms, covariance and correlation, and regression through the Data Analysis ToolPak). No programming is required — an optional R preview exists but is fully optional and not assessed. Note that the final exam is hand-calculation: you work from your note sheet, calculator and the provided tables, not a computer.
Is there a textbook for ECON 1012?
No prescribed textbook. The official outline states that no learning resources are required — the myLearning modules (concept videos, practice quizzes, tutorials and workshops) are the course material. A business-statistics textbook is suggested only as optional extra practice.
Can AI help me study ECON 1012?
Yes — Sia is an AI tutor trained on how ECON 1012 Data Analytics is actually taught and assessed at Adelaide University: it explains each formula and worked step (Z vs t, confidence intervals, regression) instead of just handing over answers. Try the free AI economics tutor, or read this guide free and ask Sia as you go.
How to study for the exam
Run ECON 1012 as a weekly loop: watch the module's concept videos, then take the practice quiz until you can score full marks — quizzes are re-attemptable with randomised questions, and the final's 25 MCQs are styled like them. Treat every workshop as case-study rehearsal: the exam's 3 case-study questions follow the workshop format, so write out full solutions — hypotheses, formula in symbols, substitution, decision rule, plain-English conclusion — instead of just reading answers. Start your A4 note sheet in Week 1 and add to it module by module: deciding what earns a place on one double-sided page is itself the revision. Guard the block transitions — inference (Weeks 4–7) reuses the descriptive block, and regression (Weeks 8–10) reuses both. In the exam window, do timed mixed practice across all ten weeks using only your note sheet, a non-wireless calculator and the Z and t tables — the exact conditions of the 180-minute paper.
