MCQs — Data and Analysis

Data is raw and unprocessed; when it is processed and given meaning it becomes information.

A dataset is an organised collection of related data, usually in table form.

Data analytics inspects and interprets data to find useful patterns and conclusions.

Data science combines statistics, mathematics and computing to obtain insights from data.

Statistics is the science of collecting, organising, analysing and interpreting data.

Probability measures the chance that an event will happen.

Machine learning lets computers learn from data instead of relying only on fixed rules.

Deep learning uses multi-layered artificial neural networks to learn complex patterns.

Data mining searches large datasets for hidden patterns and relationships.

Data visualization shows data graphically so it is easier to understand.

Data science analyses patient records to predict diseases and support treatment decisions.

Online stores and streaming services analyse user behaviour to give recommendations.

Processing and organising data gives it meaning, which turns it into information.

Charts and graphs let people spot trends quickly, which is hard with long lists of numbers.

Deep learning is a subset of machine learning that uses layered neural networks.

Searching finds something already known; data mining reveals patterns nobody specified in advance.

Statistics summarises data and probability estimates chances, which together support conclusions and predictions.

Data science is the broader field and includes modelling and prediction as well as analysis.

Calculating an average from recorded marks is analysing data to get a useful result.

Past data is analysed to predict future conditions, which is a core use of data science.