1. Understand that statistics can be used to gain information about a population by examining a sample of the population; generalizations about a population from a sample are valid only if the sample is representative of that population.

2. Understand that random sampling tends to produce representative samples and support valid inferences.

3. Use data from a random sample to draw inferences about a population with an unknown characteristic of interest.

4. Generate multiple samples (or simulated samples) of the same size to gauge the variation in estimates or predictions.

5. Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities; measuring the differences between the centers by expressing it as a multiple of a measure of variability.

6. Use measures of center and measures of variability for numerical data from random samples to draw informal comparative inferences about two populations.

2. Understand that random sampling tends to produce representative samples and support valid inferences.

3. Use data from a random sample to draw inferences about a population with an unknown characteristic of interest.

4. Generate multiple samples (or simulated samples) of the same size to gauge the variation in estimates or predictions.

5. Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities; measuring the differences between the centers by expressing it as a multiple of a measure of variability.

6. Use measures of center and measures of variability for numerical data from random samples to draw informal comparative inferences about two populations.