FLINDERS UNIVERSITY 
STAT1121: Data Science 
Final Examination Guide and Notes 2026 
 
- Part A: Topic Summary and Exam Tips 
- Part B: Practice Exam Questions and Answers 
- Part C: Sample Final Examination Paper 
- Part D: Suggested Solutions to Final Exam Paper 
 
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Flinders University - STAT1121: Data Science

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ACADEMIC YEAR 2025 - 2026

University	Flinders University
Study Level	Undergraduate
Topic Code	STAT1121
Topic Name	Data Science
Study Material	Final Examination Guide and Notes
Format	PDF
Page Length	59

Prepare for the exam with the most complete study guide available for the STAT1121: Data Science at Flinders University, including exam-style questions, and advice on common examination pitfalls. These notes provide support for learning and revision throughout the topic. This self-study set has been thoroughly updated to cover all the subject areas contained in the latest edition of the exam. The key skills are demonstrated in the context of the core topics of study with expertly written example sets of notes, followed by opportunities to learn and test your knowledge with the sample exam paper and answer key. This guide will help you to take the final examination with complete confidence.

This topic serves as an introduction to the interdisciplinary and emerging field of data science. You will learn how to combine tools and techniques from statistics, computer science and data visualisation. It aims to impart an understanding of the key issues in the analysis of statistical data together with practical experience in using a modern statistical package to perform elementary statistical analysis in a wide range of applications.

Subject areas to be covered include:

Design of experiments: experiments, observational studies, sample surveys; measurements & variables; replication & pseudo-replication.
Descriptive statistics: graphical & numerical summaries; the shape of a distribution; data screening & outliers.
Exploring relationships: predictor-response data; the least-squares line; residuals & transformations; prediction; the sample correlation coefficient; time series.
Probability: basic concepts; conditional probability & independence; random variables, the binomial distribution, the normal distribution.
Statistical inference: samples & populations; estimation, confidence intervals, hypothesis testing; inference for normal samples (one-sample); inference for proportion.
Data management: selection, sampling and cleaning; big data storage and management issues; tools and techniques for exploratory data analysis and prediction.

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BUSN3029	Investments and Portfolio Management
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BUSN3054	Taxation Law and Practice
STAT1121	Data Science

Flinders University - STAT1121: Data Science

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