S-IC - Domain

Making Inferences & Justifying Conclusions

High School Statistics & Probability · Common Core State Standards · Common Core 2010

Standard Unwrapping

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Vocabulary
random processesstatistical experimentspopulation parametersrandom samplemodeldata-generating processsimulationsample surveysexperimentsobservational studiesrandomizationdatapopulation meanpopulation proportionmargin of errorrandom samplingrandomized experimenttreatmentsparameters
Skills
  • Understand (statistics as a process for making inferences) #dok1
  • Describe (random sample from a population) #dok1
  • Decide (if a model is consistent with results from a data-generating process using simulation) #dok2
  • Explain (how randomization relates to sample surveys, experiments, and observational studies) #dok2
  • Use (data from a sample survey to estimate a population mean or proportion) #dok3
  • Develop (a margin of error through simulation models for random sampling) #dok3
  • Use (data from a randomized experiment to compare treatments) #dok4
  • Evaluate (reports based on data) #dok4
  • Use (simulations to decide if differences between parameters are significant) #dok4
Learning Targets
  • I can understand statistics as a process for making inferences about population parameters. #dok1
  • I can describe a random sample from a population. #dok1
  • I can decide if a model is consistent with results from a data-generating process using simulation. #dok2
  • I can explain how randomization relates to sample surveys, experiments, and observational studies. #dok2
  • I can use data from a sample survey to estimate a population mean or proportion. #dok3
  • I can develop a margin of error through simulation models for random sampling. #dok3
  • I can use data from a randomized experiment to compare two treatments. #dok4
  • I can evaluate reports based on data and differences between parameters using simulations. #dok4
Big Ideas
  • Statistics is a methodical process for making inferences about populations based on samples.
  • Randomization and simulation are essential techniques for evaluating the consistency of models and drawing conclusions from data.
Essential Questions
  • What is the role of random sampling in making inferences about population parameters?
  • How can simulations help determine if a statistical model is consistent with observed data?
  • In what ways do margin of error and randomization affect conclusions drawn from sample surveys?
  • How can differences between parameters be evaluated using data from randomized experiments?
  • What are the key differences and purposes of sample surveys, experiments, and observational studies in statistical analysis?