AA.DSR.2

Communicate descriptive and inferential statistics by collecting, critiquing, analyzing, and interpreting real-world data.

AA.DSR.2.1Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each. Distinguish between primary and secondary data and how it affects the types of conclusions that can be drawn.AA.DSR.2.2When collecting and considering data, critically evaluate ethics, privacy, potential bias, and confounding variables along with their implications for interpretation in answering a statistical investigative question. Implement strategies for organizing and preparing big data sets.AA.DSR.2.3Distinguish between population distributions, sample data distributions, and sampling distributions. Use sample statistics to make inferences about population parameters based on a random sample from that population and to communicate conclusions using appropriate statistical language.AA.DSR.2.4Calculate and interpret z-scores as a measure of relative standing and as a method of standardizing units.AA.DSR.2.5Given a normally distributed population, estimate percentages using the Empirical Rule, z-scores, and technology.AA.DSR.2.6Model sample-to-sample variability in sampling distributions of a statistic using simulations taken from a given population.AA.DSR.2.7Given a margin of error, develop and compare confidence intervals of different models to make conclusions about reliability.AA.DSR.2.8Summarize and evaluate reports based on data for appropriateness of study design, analysis methods, and statistical measures used.
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