Overview
Data is essential for informed decision-making and understanding trends in our society.
This guide provides fundamental knowledge to help you better navigate, interpret, and use official statistics responsibly. It explains where data comes from, how to analyse it correctly, how to communicate findings responsibly, and why seasonal adjustments matter.
How to use data correctly
Correlation is a statistical measure that indicates the extent to which the value of two or more variables move in relation to each other. Positively correlated variables tend to move in the same direction, while negatively correlated variables tend to move in opposite directions with one another.
However, it may not necessarily be the case that the change in one variable causes the change in the other. On the other hand, causation means that the change in one variable causes the other variable to change.
Example: Hot sunny weather would cause an ice-cream to melt and cause sunburn (with prolonged sun exposure). Melting ice-cream and getting a sunburn are correlated, where they tend to occur together in the hot sunny weather. If the presence of the hot sunny weather was ignored, it would be wrongly concluded that melting ice-cream causes sunburn!