Understand sampling methods, bias, and how to make valid inferences from sample data to populations.
Population: The entire group you want to study. Sample: A subset of the population that you actually measure. A good sample is representative — it reflects the characteristics of the population. Random sample: Every member of the population has an equal chance of being selected. This is the gold standard for avoiding bias.
Selection bias: The sample systematically excludes certain groups. Example: surveying only gym members about exercise habits. Response bias: People don't answer truthfully. Example: asking about illegal activities face-to-face. Nonresponse bias: Certain types of people don't respond. Example: busy people skip long surveys. Voluntary response bias: Only people with strong opinions respond. Exam…
Example: A school wants to know if students support a longer lunch. They survey students in the cafeteria during lunch. Is this a good sample?
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