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University of Colorado Boulder vía Coursera
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Data Acquisition, Risk, and Estimation

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  • Fundamentals of Sampling
    • Upon completion of this module, students will be able to classify types of sampling used for data acquisition, describe sampling error, and construct random number sequences for sampling.
  • Estimation
    • Upon completion of this module, students will be able to calculate point and interval estimates using RStudio and ROIStat.
  • Best Case / Worst Case Analysis
    • Upon completion of this module, students will be able to use point and interval estimates to determine best- and worst-case scenarios.
  • Foundations of Hypothesis Testing
    • Upon completion of this module, students will be able to plan for data acquisition to minimize risk in decision making, including sample size, effect size and power calculations.
  • Essentials for Effect Size Calculations
    • Upon completion of this module, students will be able to use return on investment calculations to determine effect size, sample size and power using RStudio and ROIStat.