What questions should you ask when presented with statistical information?

When you come across any statistical information, asking the right questions will help you understand the information better and assess its quality. 

Here are the questions you can ask to evaluate the validity, reliability, generalizability, fairness, meaningfulness, and variables of interest in a statistical study: 

1) Validity: Does the study measure what it claims to measure? 

  • Example: If a study claims to measure the relationship between daily exercise and happiness, does it use appropriate measures to quantify happiness and exercise? 

2) Reliability: Are the study’s results consistent and reproducible?

  • Example: If the study is repeated, would the results be similar? Look for any mention of repeated trials, replication, or confidence intervals that suggest the study has been tested for consistency.

3) Generalizability: Can the study’s results be applied to a broader population?

  • Example: If a study examines the effects of a new diet on a small group of people, can we expect similar results for the general population? Consider the sample size, demographic diversity, and any potential biases in the study’s design.

4) Fairness: Are the study’s methods and conclusions free from bias? 

  • Example: If a study finds a link between a specific type of food and health issues, consider if the study controlled for other factors like age, lifestyle, and genetics. Also, check for any conflicts of interest, such as funding from a company with a vested interest in the study’s outcome.

5) Meaningfulness: Do the study’s results have practical significance?

  • Example: If a study claims that a new medication reduces the risk of a particular health issue by 1%, is that difference large enough to have real-world implications? Look for effect sizes, p-values, and the practical implications of the study’s findings.

6) Variables of Interest: What are the key variables in the study, and how do they relate to each other?

  • Example: Consider how the researchers define and measure these variables in a study about the relationship between sleep and productivity. Are there any confounding variables, such as caffeine consumption, that might impact the results?