Evaluating statistical claims
- Course
- Problem-Solving and Data Analysis
- Question type
- Evaluating statistical claims
- Practice
- 6 practice questions
- Language
- Vietnamese · English
About this lesson
Evaluating statistical claims on the SAT: observational studies versus experiments, when a cause-and-effect conclusion is allowed (random assignment), when a result generalizes (random selection), confounding variables, and comparing the results of two groups.
On the Digital SAT, evaluating statistical claims is a Problem-Solving and Data Analysis skill that usually appears as a short description of a study followed by the question of which conclusion the data support. The study may be a survey, an experiment with volunteers or research on a randomly selected sample; sometimes results for two groups are given to compare.
Wrong answers usually sound reasonable because they claim more than the data show: a causal conclusion from a survey, a volunteer result stretched to everyone, or a comparison of head counts instead of rates. This lesson reduces every question to two checks, whether there was random assignment and where the sample was randomly drawn from, with a decision table for eliminating choices in seconds. It ends with 6 self-graded practice questions, each with a full explanation.
What you'll learn
- Tell an observational study from an experiment by how the question describes it.
- Use random assignment to decide whether a cause-and-effect conclusion is allowed.
- Use random selection to decide who a conclusion applies to.
- Cut overly strong choices and compare groups by rates rather than counts.
Lesson contents
- Lesson goals
- 1. Two kinds of studies
- Key terms
- 2. The decision table: what can you conclude?
- 3. Association is not causation
- 4. Comparing two groups
- 5. Common traps
- 6. Speed strategies
This lesson is part of HOCSAT Learn
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