The Australian National University · S2 2026 · FACULTY OF STATISTICS

STAT7055 Introductory Statistics for Business and Finance

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STAT7055 Overview

Introductory Statistics for Business and Finance
— A source-grounded STAT7055 guide to centre and variability, distribution shape, standardised score and the complete published assessment structure.
  • ANU Research School of Finance, Actuarial Studies and Statistics
  • Second Semester, 2026
  • a postgraduate course
  • 6 units
  • a statistics course for business, finance and related postgraduate study
  • 0% Canvas progress quiz, 30% in-person mid-semester examination, 20% individual R and RStudio assignment, and 50% in-person final examination

STAT7055 Introductory Statistics for Business and Finance develops descriptive statistics, probability, estimation, hypothesis testing, analysis of variance and regression for financial and investment data. It is taught within ANU Research School of Finance, Actuarial Studies and Statistics. It is a postgraduate course.

  • Assessment split 30% mid-semester exam, 20% R-based assignment and 50% final exam; the Canvas progress quiz carries 0%.
  • Exam control Both published examinations are in person and exclude dictionaries; the class-summary dates are earliest possible dates.
  • Inference habit Name the population, sampling structure and assumption before interpreting a probability, interval, test or regression coefficient.
  • Source wrinkle The official weekly schedule ends in the published 11-12-10 topic-number order, which this guide keeps visible.
STAT7055 · The Australian National University
An independent, AskSia-authored study guide. AskSia is not affiliated with, endorsed by, or sponsored by The Australian National University; the course code and name are used for identification only.
Assessment

How STAT7055 is assessed

ComponentWeightFormat
Canvas Progress Quiz0%Online feedback quiz in Week 6; listed date is the earliest possible date
Mid-Semester Examination30%In person; likely 60 minutes; Topics 1-6; dictionaries not permitted; not redeemable
Individual Assignment20%R and RStudio analyses reported individually through Canvas; not redeemable
Final Examination50%In person; likely 120 minutes; full semester; dictionaries not permitted

ANU publishes a 0% progress quiz, 30% mid-semester exam, 20% individual R assignment and 50% final exam. The two exam dates are labelled as earliest possible dates. No component-level pass hurdle appears in the captured class summary.

Current dates · verify in LMS

Current STAT7055 dates

DateItemControl
21 September 2026Mid-semester exam earliest possible dateANU says the actual sitting details will be supplied in Canvas.
16 October 2026Assignment dueIndividual R and RStudio report submitted through Canvas.
5 November 2026Final exam earliest possible dateConfirm the official examination timetable.

Current-offering dates captured in the official ANU class summary. Confirm changes and exact submission settings in the live LMS.

Contents · every chapter, one map

What STAT7055 covers

Start with Describing Financial and Investment Data; use Hypothesis Tests and Statistical Decisions as the turning point; finish by bringing the course together in Chi-Squared Tests for Categorical Data.

01

Describing Financial and Investment Data

centre and variability · distribution shape · standardised score · audit a financial data set before selecting any probability model or inferential procedure
02

Probability Rules and Conditional Reasoning

sample space · conditional probability · independence · translate a business event into sets and use conditional information without confusing disjointness with independence
03

Discrete Random Variables and Expected Value

discrete random variable · probability mass function · expected value · build a discrete distribution and connect expected value and variability to a repeated financial decision
04

Continuous Distributions and Probability Areas

continuous random variable · probability density · normal distribution · convert a continuous model into interval probabilities and interpret the role of location and scale
05

Sampling Distributions and Standard Error

random sample · sampling distribution · standard error · separate variation among observations from variation among repeated sample statistics
06

Estimation and Confidence Intervals

point estimate · confidence interval · margin of error · construct and interpret an interval while showing the estimate, uncertainty and model conditions separately
07

Hypothesis Tests and Statistical Decisions

null and alternative hypotheses · test statistic · p-value and decision · state hypotheses, evaluate compatibility with the null model and separate the statistical decision from the business conclusion
08

Comparing Two Populations

independent groups · paired observations · standard error of a difference · choose an independent or paired comparison from the data-generating structure and interpret the estimated difference
09

Analysis of Variance Across Groups

between-group variation · within-group variation · F statistic · use an F comparison to test group-mean evidence and plan follow-up comparisons without inflating error
10

Simple Linear Regression

response and explanatory variables · least-squares slope · residual · fit and interpret a one-predictor regression while checking units, residual patterns and extrapolation
11

Multiple Linear Regression

partial regression coefficient · confounding · model fit · interpret a coefficient conditionally and test whether adding predictors changes precision, bias risk and substantive meaning
12

Chi-Squared Tests for Categorical Data

contingency table · expected count · chi-squared statistic · compare observed and expected counts to assess categorical association and locate influential cells

It carries 6 units. It is positioned as a statistics course for business, finance and related postgraduate study.

The 2026 class sequence moves from describing a data set to reasoning about random variables and sampling, then to inference and regression.

A zero-weight Canvas quiz supplies progress feedback before the two examinations and the R-based assignment.

Assessment in STAT7055 is distributed as follows: 0% Canvas progress quiz, 30% in-person mid-semester examination, 20% individual R and RStudio assignment, and 50% in-person final examination

The operational assessment conditions matter here.

The mid-semester examination is likely 60 minutes, in person and covers Topics 1-6; the final is likely 120 minutes, in person and covers the full semester.

Dictionaries are not permitted in either examination, and the listed dates are earliest possible dates rather than guaranteed sittings.

What makes STAT7055 demanding is concrete: Choosing an inferential method from the sampling structure, carrying its assumptions through the calculation, and translating the numerical output into a conclusion that remains about the stated population and business or finance question.

No component-level pass hurdle is published in the captured class summary.

The mid-semester exam and assignment are described as not redeemable; students must confirm any later operational rule in Canvas.

For enrolment planning, Confirm eligibility in the current ANU Programs and Courses entry; the captured class summary does not publish a prerequisite statement.

Start with Describing Financial and Investment Data; use Hypothesis Tests and Statistical Decisions as the turning point; finish by bringing the course together in Chi-Squared Tests for Categorical Data.

Coverage note: the official schedule labels the final three teaching entries Topic 11, Topic 12 and Topic 10 in that order; this guide preserves the published teaching order and does not silently renumber it.

Worked example · free

From a finance sample to a bounded confidence statement

Q [5 marks]. An AskSia-authored sample of 36 monthly returns has mean 1.4% and sample standard deviation 3.0%. Construct an approximate 95% interval using 1.96 and interpret it without claiming certainty.
  • 1Compute the standard error as 3.0% divided by the square root of 36, giving 0.5%.
  • 1Compute the approximate margin 1.96 times 0.5%, giving 0.98%.
  • 1Form the interval 1.4% plus or minus 0.98%, or about 0.42% to 2.38%.
  • 1Tie the interpretation to the sampling procedure and the target mean rather than to individual months.
  • 1State that dependence, selection or a poor model can invalidate the approximation.
Under the stated independent-sample approximation, the procedure gives about 0.42% to 2.38% for the target mean return. It does not say that 95% of monthly returns lie in that interval or that this realised interval has a 95% posterior probability.
Sia tip — Keep percentage points distinct from percentage changes and state the sampling assumptions.
Glossary

Key terms

Sampling distribution
The probability distribution of a statistic across repeated samples drawn under the same design.
Analysis of variance
A method that partitions variability to compare group means under a stated statistical model.
Multiple linear regression
A linear model relating one response variable to two or more explanatory variables simultaneously.
Descriptive statistics
Numerical and graphical methods used to summarise the location, spread and shape of observed data.
Random variable
A rule that assigns a numerical value to each outcome of a random process.
Probability distribution
A specification of the possible values of a random variable and their associated probabilities.
Confidence interval
A range calculated by a procedure designed to capture an unknown parameter at a stated long-run rate.
Hypothesis test
A decision procedure that evaluates sample evidence against a specified null model and significance rule.
Chi-squared test
A test comparing observed categorical counts with counts expected under a specified null relationship.
Simple linear regression
A linear model relating one response variable to one explanatory variable through an intercept and slope.
Standard error
The standard deviation of a statistic's sampling distribution, estimating its repeated-sample variability.
FAQ

STAT7055 FAQ

Which current STAT7055 dates are captured?

Mid-semester exam earliest possible date: 21 September 2026; Assignment due: 16 October 2026; Final exam earliest possible date: 5 November 2026. Confirm any change and the exact submission setting in the live LMS.

Where do students usually lose marks in STAT7055?

Choosing an inferential method from the sampling structure, carrying its assumptions through the calculation, and translating the numerical output into a conclusion that remains about the stated population and business or finance question.

What is the STAT7055 exam or final-task format?

The mid-semester examination is likely 60 minutes, in person and covers Topics 1-6; the final is likely 120 minutes, in person and covers the full semester. Dictionaries are not permitted in either examination, and the listed dates are earliest possible dates rather than guaranteed sittings.

Does STAT7055 have a hurdle or component-level pass rule?

No component-level pass hurdle is published in the captured class summary. The mid-semester exam and assignment are described as not redeemable; students must confirm any later operational rule in Canvas.

What prerequisites or restrictions apply to STAT7055?

Confirm eligibility in the current ANU Programs and Courses entry; the captured class summary does not publish a prerequisite statement.

Is this STAT7055 resource an official university guide?

No. It is an independent STAT7055 study resource; current institutional instructions remain authoritative for assessment operation.

Study strategy

How to study for the exam

Retrieve the course map, practise the recurring method—identify the population and variables, select a probability or inferential model from the sampling structure, calculate transparently and translate the result into a qualified finance or business conclusion—on changed scenarios, and verify every operational assessment detail in the live institutional system.

Study STAT7055 with AI

Your AI Statistics tutor for STAT7055

Stuck on a hard STAT7055 question? Sia is AskSia’s AI Statistics tutor — ask any STAT7055 Introductory Statistics for Business and Finance question and get a clear, step-by-step explanation grounded in how the course is actually taught and assessed. Read this whole study guide free, then take your hardest questions to Sia.

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