Software Engineering › Learn step by step › Y12 Software Automation
Item 312 of 426 · Year 12: Software Automation, 19 of 35
Logistic regression
Term Key terms bank
Jump to a topic
- Exam format, question types and command words (46)
- Year 11: Programming Fundamentals (69)
- Year 11: The Object-Oriented Paradigm (33)
- Year 11: Programming Mechatronics (29)
- Year 12: Secure Software Architecture (57)
- Year 12: Programming for the Web (59)
- Year 12: Software Automation (35)
- Year 12: The Software Engineering Project (47)
- Diagrams and modelling tools (18)
- Python, SQL, pseudocode and CSS patterns (33)
Definition
Predicts the probability of a category (yes or no) and so is used for classification, not for predicting a number.
Example: Predict whether an email is spam.
Found in: syllabus, course specifications, 2025 HSC marking guidelines, school notes.
Classification (yes/no) using probability.
Where you'll use it in the test
Syllabus area: Y12 Software Automation.
Question types it can appear in
- Multiple choice: 2025 Q12: true or false statements
- Short answer: Define, outline or explain it and tie it to the scenario.
- Python: Write or complete it in the online Python tool.
Where it has appeared in the paper
Software Automation (Part A). Part letters follow each paper’s own layout.
Related past questions
- 2025 HSC Q12 (2 marks): Logistic regression Software Automation (Part A) · 2 marks
How to use it
A model sentence
“Predicts the probability of a category (yes or no) and so is used for classification, not for predicting a number.” Then apply it: Predict whether an email is spam.
In a short answer, give the definition in your own words first, then tie it to the situation in the question. Do not copy the example above unless it fits the scenario.
Command words used with it
No linked question shows the command word for this term. Across the past short answer and python questions in this bank the words used most are: Explain, Outline, Describe, Compare, Classify, Analyse. Check the actual word in your question.
Official worked answer
2025 HSC Q12 (2 marks): Logistic regression (2 marks): official criteria and sample answer
Criteria
2: True or false correct for all SIX check boxes. 1: Correct for FOUR of the six.
Sample answer
True: spam, two-party election outcome, university admission (all yes/no classification). False: house prices, height v weight, spread rate (continuous values: linear/polynomial regression).
Go deeper
- Flashcard: Logistic regression in Software Automation (Year 12) · study that set
- Memorise: Decision trees
- Key terms bank entry: Logistic regression
- Notes: Describe types of algorithms associated with ML, including linear regression, logistic… (Software Automation (Year 12))
- Notes: Design, develop and apply ML regression models using an OOP to predict numeric values,… (Software Automation (Year 12))
- Master answer: hsc2025-q12 (2 marks, multi-select (true/false check boxes)) (Master model answers: Software Automation)
- Full term page: every question, note and marking comment for Logistic regression
Check yourself
Explain “Logistic regression” in one sentence, give an example, and name a question type that could test it.
Reveal the answer
Predicts the probability of a category (yes or no) and so is used for classification, not for predicting a number.
Example: Predict whether an email is spam.
Could be tested as: Multiple choice, Short answer, Python.
Quick multiple choice select all that apply
(Tick the scenarios marked TRUE in the NESA answer. Original stem not published; the task is reconstructed from the marking guideline: which scenarios suit logistic regression?)
- Identifying whether a received email is spam
- Determining the outcome of a two-party election
- Calculating house prices based on land size
- Investigating the relationship between height and weight
- Estimating the rate at which a contagious illness will spread
- Working out if someone will be admitted to a university course
Show the answer
A, B, F
Logistic regression handles yes/no classification. House prices, height v weight and rate of spread are continuous numeric predictions (linear/polynomial regression). Stem wording not published by NESA.
Source: NESA 2025 HSC Software Engineering exam (online) - Marking Guidelines. Open it in the multiple-choice bank.