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VCE Data Analysis · Modules 25–37

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A free printable VCE Data Analysis definitions worksheet with 10 key terms, built from the key terms of Data types and data characteristics to Privacy and the Australian Privacy Principles (Modules 25–37) — Characteristic of data: accessibility, Characteristic of information: clarity, Characteristic of information: context, Data quality: accuracy, Data quality: bias, Data quality: relevance and more. Print it or save it as a PDF — the answer key starts on its own page. No login needed.

VCE Data Analysis Definitions Worksheet: Data types and data characteristics to Privacy and the Australian Privacy Principles (Modules 25–37)

Name:
Date:
Class:

Key terms

Write what each term means, in your own words.

1
Accessibility
2
Clarity
3
context
4
accuracy
5
biased data
6
relevant data
7
reliability
8
data quality check
9
sensitive information
10
Australian Privacy Principles (APPs)

Answer Key

VCE Data Analysis · Modules 25–37 · Student wording will vary for definitions
1Accessibility — How easily the people who need data can find it, open it and use it, including having the right file format, the right permissions and support for users with disability.
2Clarity — Information has clarity when it is easy to understand and not ambiguous, thanks to clear headings, labels, units and wording (e.g. 'Height (cm)' not 'Size').
3context — The background to data, such as who collected it, when, where and why, which gives the data its meaning. Without it, data can be misread.
4accuracy — Data is accurate when it is correct and free from errors, so it matches the real-world fact it records. Typos, faulty measurements and out-of-date values make data inaccurate.
5biased data — Data that unfairly favours one view or group because of how it was collected or selected, e.g. sampling bias, leading questions or missing groups.
6relevant data — Data that relates directly to the question or purpose it is used for. Unneeded fields or data from the wrong population are not relevant, so they lower the quality of the information.
7reliability — Data is reliable when it comes from a trustworthy source and gives consistent results if collected again in the same way. A larger sample size also makes results more reliable.
8data quality check — Judging a dataset by testing accuracy, bias, integrity, relevance and reliability one at a time, and using evidence to show how any problem could affect conclusions.
9sensitive information — A special kind of personal information, like health, ethnic origin, religion or biometric data, that the Privacy Act protects more strictly because misuse can cause serious harm.
10Australian Privacy Principles (APPs) — 13 legal principles in the Privacy Act 1988 that set rules for how organisations collect, use, store, give access to and correct personal information. Use them as a checklist.

Modules this definitions worksheet covers

Every module has its own free printable worksheet with an answer key, and students can practise the same terms interactively on Cloodit.

Part of: VCE Applied Computing - U1O1 - Data analysis, VCE Data Analytics - U3O1 - Data Analytics, VCE Data Analytics - U3O2 - Analysis and Design, VCE Data Analytics - U4O1 - Development and Evaluation, VCE Data Analytics - U4O2 - Cyber Security: Data Security, 9-10 Digital Technologies: Data privacy and the Australian Privacy Principles, ACARA Digital Technologies Years 7–8 — Acquiring and Storing Data, ACARA Digital Technologies Years 7–8 — Digital Footprints and Data Minimisation, ACARA Digital Technologies Years 9–10 — Acquiring and Validating Data, ACARA Digital Technologies Years 9–10 — Privacy Principles and Digital Footprints, QCE Digital Solutions Unit 2 — Data-Driven Problems and Solution Requirements, QCE Digital Solutions Unit 2 — Data and Programming Techniques, QCE Digital Solutions Unit 2 — Prototype Data Solutions, QCE Digital Solutions Unit 4 — Digital Methods for Exchanging Data, QCE Digital Solutions Unit 4 — Complex Digital Data Exchange Problems and Solution Requirements, WA Computer Science ATAR Year 11 — Data Management

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