What is the science of statistics?
The science of data
In a data-rich world, every person needs to be a data scientist.
What is a data scientist often referred to as?
A data story-teller
This emphasizes the role of communicating insights derived from data.
What are the key skills required in Data Science?
- Statistical thinking
- Computational skills
- Curiosity
- Collaboration
- Clear communication
These skills are essential for effective problem solving with data.
What challenges in data science require integrity and transparency?
Ethics and privacy
These challenges are consistent with Australian and global regulations.
Why is the design of a statistical study critical?
To obtain results that can be trusted, understood, and generalised
A well-designed study enhances the validity of the findings.
What is the best method for assessing a new treatment?
Randomised controlled trial (RCT) with double-blinding
This method minimizes various biases but is often not feasible.
What biases does a randomised controlled trial (RCT) help to minimise?
- Selection bias
- Observer bias (including the placebo effect)
- Confounding (lurking variables)
Minimizing these biases is crucial for the reliability of study results.
Most statistical studies involve observational data. What does this mean?
Data is in the form it appears in, rather than in a form designed by the investigator
This requires careful interpretation to avoid errors.
What is a common interpretation error in statistics that involves confusing association for causation?
Misleading confounders
Historical controls can often lead to such errors.
What is Simpson’s Paradox?
A phenomenon where a trend appears in different groups of data but disappears or reverses when these groups are combined
This paradox highlights the importance of careful data interpretation.
