Teaching

I’ve been teaching graduate biostatistics since 2015 — first at Eastern Virginia Medical School, and at Old Dominion University since 2018. Across both institutions I’ve developed and taught more than 40 course offerings in applied biostatistics, statistical reasoning, research methods, and public-health methodology.

Current courses at ODU

At the Joint School of Public Health, I currently develop and teach:

• MPHO 605 — Introduction to Biostatistics (graduate, MPH core)
• MPHO 712 — Applied Biostatistics (graduate)
• MPH 612 — Statistical Reasoning for Public Health (graduate)
• MPH 616 — Research Methods in Public Health (graduate)
• MPH 713 — Applied Statistical Programming (graduate)
• CHP 711 — Applied Biostatistics for Health Research (graduate)
• CHP 445 / PUBH 445 — Health Services Research (undergraduate/graduate)

I’ve also taught biostatistics and research-methods courses at EVMS, statistical thinking at St. Cloud State, and short courses on study design, data management, and big data for biomedical sciences at the EVMS Research Boot Camp.

Teaching philosophy

I teach biostatistics the way I wish I’d been taught: effect sizes first, hypothesis tests second. A p-value is a single binary decision; an effect size with a confidence interval is a story about magnitude, precision, and uncertainty — which is what public-health research is actually about.

In practice this means:

• No test in isolation. Every test comes with its effect-size partner — Cohen’s d for t, Cramér’s V for chi-square, odds ratios for 2×2. The test answers “could this be chance?”; the effect size answers “does it matter?”
• Assumptions get equal airtime. Normality, independence, variance — we check them, and when they fail we talk about what to do instead. Students leave knowing that a Wilcoxon is not scary.
• Interpretation is a writing skill. Half the assessment is writing plain-English interpretations of statistical results for public-health audiences. If you can’t explain what p = 0.04 means to a policymaker, you haven’t learned it.

This framing follows the American Statistical Association’s 2016 statement on p-values, the GAISE 2016 recommendations, and Geoff Cumming’s New Statistics. None of it is original to me — what I’ve added is a set of open tools that make it practical for students to do the right thing without needing a stats package on day one.

This approach was recognized with the ASA Outstanding Teaching Award from the Teaching of Statistics in the Health Sciences Section in 2023, and the Crystal Apple Award for Teaching Excellence from the EVMS Student Government Association in 2018.

Open tools — the Z-t-Chi Calculator

The Z-t-Chi Calculator is a free, browser-only biostatistics toolkit I built for my MPHO 605 students and released publicly. It covers:

• Z-tests, t-tests (one/two-sample, paired, Welch)
• Chi-square and Fisher exact tests with effect-size partners (Cramér’s V, phi)
• Epidemiology 2×2 — risk ratio, odds ratio, sensitivity, specificity, PPV/NPV with confidence intervals
• Multiple-comparison corrections — Bonferroni, Holm, Benjamini-Hochberg with a live Type I inflation visualization
• Sampling-distribution simulations for building CLT and p-value intuition
• Assumption Coach — Shapiro-Wilk, Jarque-Bera, visual checks

No ads, no tracking, no signup. All math runs in the browser. Source code is public on GitHub — instructors can fork it, students can audit it, anyone can verify the formulas.

Student mentoring

Since 2015:

• 106 MPH students advised academically
• 11 MPH students as practicum preceptor/advisor
• 11 MPH and PhD students whose research projects I’ve directly supervised
• 5 medical students supervised on research
• 11 dissertation committees (4 as chair)

Chairing dissertations gives me the same kind of satisfaction as proving a clean theorem — watching someone frame a research question, negotiate an imperfect dataset, and reach a defensible answer is the best part of the job.

Guest teaching & short courses

• EVMS Research Boot Camp — Study Design, Data Management, and Statistical Analysis (Summer 2016, 2017); Big Data in Biomedical Sciences (Spring 2018)
• Multiple guest lectures across ODU, VCU, and EVMS programs.

For instructors adopting the calculator

If you’d like to use Z-t-Chi in your own course, the instructor builder at teach.hgaladima.com (private, invitation-only) lets you create signed problem links for your students. Email me if you’d like access — it’s free and non-commercial.