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Section 13.4 Summary of What You Have Learned in This Chapter

  • How to construct a two-way table
  • Examining conditional proportions to explore group differences on a categorical response variable
  • How to construct and interpret a segmented bar graph
  • How to state hypotheses in terms of the difference in two population proportions
  • When and how to use technology to apply two-sample z procedures to compare two sample proportions
  • Interpretation of the z-confidence interval as the interval of plausible values for the difference in the population proportions or process probabilities
  • Terminology of observational studies and experiments, including explanatory and response variables
  • Being able to distinguish between observational studies and experiments
  • Identifying and explaining potential confounding variables in observational studies
  • How to carry out random assignment
  • The benefits of random assignment
  • Approximating p-values using a two-way table simulation
  • Calculating exact p-values using the hypergeometric distribution
  • Using the normal approximation to obtain p-values and confidence intervals for an underlying treatment effect (when and how)
  • Factors that affect the statistical significance between the two groups (e.g., sample size, size of treatment effect)
  • Distinctions between cohort, case-control, and cross-classified studies
  • Distinctions (and equivalences) between relative risk and odds ratio (how to calculate, how to interpret)
  • Confidence intervals for relative risk and odds ratios
  • Limitations in the scope of conclusions that can be drawn from different study designs
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