Software Engineering › Key terms › Y12 Software Automation › Data analysis and forecasting
Data analysis and forecasting
Definition
ML finds trends in past data to predict future values (sales, weather, demand).
Example: Forecast next month's electricity demand.
Found in: syllabus, sample exam and familiarisation guidelines, school notes.
Where it is used in the test
Syllabus area: Y12 Software Automation.
Question types it can appear in
- Short answer: Define, outline or explain it and tie it to the scenario.
- Extended response: Use it as a supporting point linked to the stimulus.
- Multiple choice: Pick the option that matches the definition or example.
Where it has appeared in the paper
Software Automation (Part B). Part letters follow each paper’s own layout.
Related past questions
- Sample exam Q15 (3 marks): Machine learning in data analysis Software Automation (Part B) · 3 marks
These are the questions the flashcard set links to this term. Open each one and compare your answer with its marking criteria.
Study links
- Flashcard: Data analysis and forecasting in Software Automation (Year 12) · study that set
- Memorise: Applications of key ML algorithms
- Notes: Investigate common applications of key ML algorithms, including data analysis and… (Software Automation (Year 12))
- Notes: Applications of key ML algorithms (Software Automation (Year 12))
How to use it in an answer
A model sentence
“ML finds trends in past data to predict future values (sales, weather, demand).” Then apply it: Forecast next month's electricity demand.
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
- Describe: Provide characteristics and features. (Sample exam Q15 (3 marks): Machine learning in data analysis)
Technique for the question types
- Short answer: One clear point per mark, use the stimulus and course terms, and answer the command word.
- Extended response: Plan with the command word, give a judgement or explanation supported by named details from the stimulus, use course terms and cover both sides when asked.
- Multiple choice: Read all four options, rule out wrong ones, pick one; no penalty for guessing so never leave blank.
Worked answers from the marking guidelines
Sample exam Q15 (3 marks): Machine learning in data analysis (3 marks): criteria and sample answer
Criteria
3: Describes how ML algorithms can be used in data analysis. 2: Outlines some features of ML algorithms relevant to data analysis. 1: Some relevant information.
Sample answer
Machine learning algorithms can be trained with a subset of the data to automatically identify patterns and trends within large datasets. The algorithms can handle complex relationships and nonlinearities present in the data allowing for efficient and comprehensive analysis. Machine learning can also be used for predictions and forecasting. These models can learn from new data over time, continuously improving their analysis and predictive accuracy and performance.
Common mistakes
- Use the term exactly as the syllabus words it, then link it to the scenario in the question; the 2025 feedback repeatedly rewards using the stimulus.
- Answer the command word: outline gives main points only, explain gives a reason or cause, discuss gives both sides.
Related terms
Same group in the syllabus: Virtual personal assistant · Image recognition