Lesson objective: Understand that randomness of sampling is essential to making inferences.

Students bring prior knowledge of summarizing numerical data sets in relation to their context, such as by describing the nature of the attribute under investigation, including how it is measured and its units of measure from 6.SP.5b. This prior knowledge is extended to analyzing how data is acquired as students develop methods of random sampling. A conceptual challenge students may encounter is choosing a biased sample and saying it is random.

The concept is developed through work with written representations, which defends one’s stance on which is most random.

This work helps students deepen their understanding of equivalence because maintaining an equal chance of selection and unbiased data helps provide a more random sample of the population.

Students engage in Mathematical Practice 3 (Construct viable arguments and critique the reasoning of others) as they analyze and critique various methods of sampling and their degree of randomness.

**Key vocabulary:**

- random
- sample
- representative
- bias

**Special materials needed:**