Bivariate Statistics

Bivariate Statistics

This lesson focuses on describing and summarizing your data by groups and/or looking at bi-variate associations given the type of each variable:

• continuous - continuous
  • Pearon’s R
  • Spearman’s rho (non-parametric)
  • Kendall’s Tau (non-parametric)
• continuous - ordinal (or ordinal - ordinal)
  • Spearman’s rho (non-parametric)
  • Kendall’s Tau (non-parametric)
• categorical - ordinal or continuous
  • 2 independent groups
    • t-test
    • Mann Whitney (non-parametric) test
  • 3 or more independent groups
    • ANOVA
    • Kruskal-Wallis (non-parametric ANOVA)
• categorical - categorical
  • Chi-square tests (when <20% of cells have expected counts < 5)
  • for 2x2, Fisher’s Exact Test (when 20%+ cells have expected counts < 5)
  • for rxc, Fisher-Freeman-Halton Test (when 20%+ cells have expected counts < 5)

The HELP Dataset

We are still working with the HELP (Health Evaluation and Linkage to Primary Care) dataset. See details at https://melindahiggins2000.github.io/N736Fall2017_lesson07/lesson07_univStats.html.

R Code

Run examples shown in lesson08_Rcode.R

SAS Code

Run examples shown in lesson08_SAScode.sas