# Evaluating Statistical Claims on the SAT: Examples & Practice Source: https://1600.now/sat-skill/evaluating-statistical-claims --- Math · Problem-Solving and Data Analysis ## Evaluating Statistical Claims Check two separate permissions: random sampling supports generalizing to a population, while random assignment in a well-designed experiment supports a causal comparison. A large sample alone supplies neither. Written by [Luke Finigan](https://1600.now/about) 2 min read Updated Oct 2, 2026 ### Ask how the participants were selected A survey randomly selects 300 people from a town's resident list. Its results can support an estimate for that town's represented population, subject to sampling uncertainty and study limitations. A poll answered by 300 visitors to a fitness website has a different selection process. The number 300 does not make the second sample representative. Volunteers may differ from nonvolunteers. In statistical claims analysis, first identify the target population and then ask whether the selection method reaches it fairly. ### Ask how treatments were assigned Researchers randomly assign volunteers to a new tutoring program or an existing program and compare their later results. Random assignment helps balance other differences between groups and supports attributing an observed treatment difference to the intervention, within the experiment's limitations. Choosing which program to attend is not random assignment. Students who choose extra tutoring might differ in motivation, prior preparation, or available time. Those differences can confound a causal explanation. ### Keep generalization separate from causation An observational study might randomly sample residents and find that those who walk more report better sleep. It can describe an association in that population, but it does not establish that walking caused the sleep difference. An experiment using volunteers may support a causal comparison for its participants while having limited justification for generalizing to everyone. A study can earn one kind of conclusion without earning the other. ### Match the claim's scope to the design If a study samples one school's students, a choice claiming the result applies to every teenager expands the population beyond the evidence. If it only records behavior, a choice claiming a treatment caused an outcome expands association into causation. Underline the claim's population and causal verb. Compare each with the study design before considering whether the result sounds plausible. A plausible explanation is not a substitute for the needed evidence. ### Check your understanding Try it yourself A random sample of residents shows that people who bike more have lower reported stress. What is supported? A Biking causes lower stress. B Stress causes people to bike less. C Biking and reported stress are associated in the sampled population. D Every resident who bikes has low stress. Evaluating Statistical Claims · Hard For a study, a group of squirrels will be selected from a habitat consisting of 240 squirrels, and a group of groundhogs will be selected from a habitat consisting of 210 groundhogs. Some of the squirrels and groundhogs will be in a treatment group, and some of the squirrels and groundhogs will be in a control group. Which of the following is necessary for this study to attempt to establish a cause-and-effect relationship between two variables? A The number of squirrels in the treatment group is equal to the number of groundhogs in the treatment group, and the number of squirrels in the control group is equal to the number of groundhogs in the control group. B The squirrels and the groundhogs are randomly assigned to the treatment and control groups. C The squirrels and the groundhogs are randomly selected from their respective habitats. D The average age of the squirrels in the treatment group is equal to the average age of the groundhogs in the treatment group, and the average age of the squirrels in the control group is equal to the average age of the groundhogs in the control group. - [Open the question and explanation](https://1600.now/bank/math/7f59c954) ### Practice this skill 1. Label a study observational or experimental. 2. Mark random sampling and random assignment separately. 3. Rewrite an overbroad claim so its population and causal language fit the design. [Practice evaluating statistical claims](https://1600.now/bank/math/skill/Evaluating%20statistical%20claims%3A%20Observational%20studies%20and%20experiments) [Print the evaluating statistical claims worksheet and worked answers](https://1600.now/sat-evaluating-statistical-claims-worksheet). Then use a [mixed practice module](https://1600.now/modules) to check whether you can choose this method among other question types. ### Source and question labels The bank label for this guide is "Evaluating statistical claims: Observational studies and experiments" in Problem-Solving and Data Analysis. The worked examples above are written for this guide. - [College Board: Types of Math tested](https://satsuite.collegeboard.org/sat/whats-on-the-test/math/types) ### Related skills - **[Inference from Sample Statistics and Margin of Error](https://1600.now/sat-skill/sample-statistics-margin-of-error)** A sample estimates a population quantity. - **[Two-Variable Data: Models and Scatterplots](https://1600.now/sat-skill/two-variable-data)** A scatterplot compares paired variables. - **[Command of Evidence](https://1600.now/sat-skill/command-of-evidence)** Identify the claim before selecting evidence.