Reading Statistics in Research and News
Judge a study or headline claim with a short list of sharp questions
A taste of a lesson
A headline says eating a certain snack daily 'raises cancer risk by 40 percent'. Should I worry?
Let us ask three questions before worrying. First, 40 percent of what? If the baseline risk is 5 in 1,000 over ten years, a 40 percent rise means 7 in 1,000, two extra cases per 1,000 people. Second, what kind of study? If it compared people who already ate the snack with those who did not, other habits may explain the difference. Third, is it one study or a consistent pattern? Can you find the baseline risk in the article, or is it missing?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Identify a study's design and what it can and cannot show
- Find the sample, comparison and absolute effect behind a claim
- Spot common headline exaggerations and statistical red flags
- Weigh a single study against the wider evidence
- Summarise a claim with calibrated, honest language
Lesson plan
- 1 From headline to source Trace a claim back to the actual study and read its abstract. Start
- 2 Study designs and what they show Match study designs to the strength of claims they support. Start
- 3 The numbers that matter Find sample size, absolute effects and uncertainty. Start
- 4 Red flags Recognise warning signs of overreach or selective reporting. Start
- 5 One study among many Place a finding within the wider body of evidence. Start
- 6 Saying it honestly Summarise a claim with calibrated language and clear caveats. Start
Try asking
About this tutor
A tutor for any level that teaches you to read statistical claims critically, from news headlines to research abstracts and company reports. You will learn the main study designs and what each can show, how to find the effect size and sample behind a claim, and the warning signs of overreach: relative risks without baselines, surrogate outcomes, cherry picked comparisons and single studies treated as settled. Bring articles you are curious about and the tutor will help you take them apart. No maths required, though experienced learners can go deeper into methods.
Reviews
4.7
3 ratingsSample
- Jean-Luc M.Sample
As a researcher I appreciated the deeper methods discussion. Fair to observational studies, which many courses are not.
- Wren T.Sample
Calm and balanced. It made me less cynical and more careful at the same time.
- Nkechi U.Sample
I bring a health headline to each session and we take it apart. The 'risk per 1,000' question alone has changed how my family reads the news.
About the teacher
Statistics in plain language, from averages to Bayesian reasoning
9 tutors 350 lessons taught Sample
I teach statistics to people who were put off by it the first time. My approach is to start from a question someone actually has, simulate or count our way to an answer, and only then name the formula. I have worked as an analyst on survey and health research projects, so I have a soft spot for messy samples,...
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