Schedule (workflow flow)
A 15-week pacing plan — Blackboard is authoritative for dates and deadlines
This is a pacing plan, not a calendar. It shows the order in which the SAS analytics workflow unfolds — from the environment, through building and validating data, into summaries and statistical procedures, and on to simulation and reproducible reporting — and roughly when, so you can read ahead and see where you are headed. It is not the authoritative calendar: exact dates, deadlines, submission windows, and any mid-term adjustments live in Blackboard (the LMS), which is authoritative. A few fixed semester dates are noted for orientation only — confirm everything against Blackboard.
The course runs fifteen weeks in four parts. Each part below lists its weeks, the theme for each week, and the throughline — the workflow move that carries the week, in the spirit of the recurring question “would someone else be able to understand, rerun, and verify this?” The theme links to that week’s note. The single recurring teaching dataset is the synthetic, observational wellness-program study (“RiverCity Wellness”); it is synthetic; seed set (streaminit(20260824)) and is not real health data.
Nothing on this site was run in SAS. SAS is proprietary and is not executed in this build, so every SAS program, log excerpt, and PROC output table you will meet in the weekly notes is hand-authored and synthetic (verified: false). A rendered, syntax-highlighted listing is not evidence that the code runs or that the numbers are right. See each page’s Verification & reproducibility status section, and the the course’s private notation and verification ledger §5 for the pending human/SAS-run sign-off.
Part I — The SAS analytics environment (Weeks 1–3)
We set up the frame: what SAS is for as a professional analytics environment, how to open a project and write a first program, and how libraries, datasets, variables, and formats organize the data you will analyze.
| Week | Theme | The throughline |
|---|---|---|
| 1 | What SAS is for now | What does a professional SAS analytics workflow look like — from messy data to a documented, rerunnable result — and what does the log tell you? |
| 2 | SAS environment & project setup | How do you open SAS Studio, point a libname at your data, and run a first program so the log and output are reproducible? |
| 3 | Libraries, datasets, variables & formats | How are libraries, datasets, variable attributes, and the format-vs-informat distinction the vocabulary the rest of the workflow rests on? |
Note: Labor Day (Mon, Sep 7) falls in Week 3 — no class that Monday, so the week runs Wednesday and Friday (compressed).
Part II — Building & validating data (Weeks 4–6)
We move from messy input to analysis-ready, trustworthy tables: DATA step logic, importing and cleaning, and joining two related tables — always reading the log and checking the row counts before we trust anything.
| Week | Theme | The throughline |
|---|---|---|
| 4 | DATA step logic | How does the DATA step let you create, clean, and subset data — handling the age = 199 typo, missing values, and IF/THEN logic — and what does the log confirm? |
| 5 | Importing, cleaning & validating | How do you import 210 raw rows, validate them down to 200 clean participants, and verify type problems and row counts rather than trusting the output? |
| 6 | PROC SQL & joins | When you join participants to screenings, why is an inner join 594 rows but a left join 596 — and why must you check the row count after every join? |
Part III — Summaries, output & statistical procedures (Weeks 7–11)
We summarize and report, then run the core statistical procedures — t-tests, ANOVA, regression, logistic regression — always stating assumptions and naming what the result does and does not show.
| Week | Theme | The throughline |
|---|---|---|
| 7 | Summaries, tables (+ midterm) | How do PROC MEANS, FREQ, and UNIVARIATE summarize the study — and why is the mean of a 0/1 variable a proportion? |
| 8 | Visualization & ODS output | How do SGPLOT and the ODS destinations turn an analysis into report-ready, text-described graphs and tables? |
| 9 | t-tests, ANOVA & group comparisons | How do PROC TTEST (systolic_bp by arm) and PROC GLM (by site) compare groups — and which assumptions must hold first? |
| 10 | Linear regression | How does PROC REG model systolic_bp from age and baseline_bmi, and what do \(R^2\), RMSE, and the residual checks tell you? |
| 11 | Logistic regression & categorical outcomes | How does PROC LOGISTIC model whether a participant met goal, which level is the event, and why is an odds ratio not a risk ratio? |
Note: the midterm practical is Friday, Oct 9 (in class), during Week 7. It covers the SAS environment, project setup, libraries, datasets, variable attributes, the DATA step, importing, cleaning, validation, PROC SQL, summaries, and reporting. No graded content appears on this public site — see Blackboard.
Part IV — Shaping, simulation & reproducible reporting (Weeks 12–15)
We reshape and merge data, use simulation to study how procedures behave, then assemble the whole pipeline as one reproducible, verifiable analysis report and review the entire workflow.
| Week | Theme | The throughline |
|---|---|---|
| 12 | Reshaping & merging data | How do PROC TRANSPOSE (wide↔︎long) and a keyed MERGE reshape and combine data without silently creating a many-to-many bug? |
| 13 | Simulation & random generation | With streaminit(20260824) and RAND, how do you simulate datasets to study power (≈ 0.99), Type I error (≈ 0.05), and a sampling distribution? |
| 14 | Reproducible SAS analysis report | How do you assemble the full pipeline — question → analysis-ready data → procedures → output → verification — as one program another person could rerun? |
| 15 | Final analytics project & review | How do the import, validation, summary, procedure, simulation, and reporting steps fit together as one reliable, traceable analytic practice? |
Note: fall break is Nov 22–28 (no classes), between Weeks 13 and 14. The last class is Mon, Dec 7, the consultation day is Dec 8, and the final-exam window is Dec 9–15 (exact block via Blackboard).
How the week rhythm works
Each week follows the same three-day rhythm so the workflow habit becomes automatic:
- Monday — concept + syntax: the week’s idea and the SAS code that carries it.
- Wednesday — build + debug: read the log, debug the code, inspect the output.
- Friday — skill check + applied analytics task: put the move to work on a new slice of the study.
The discipline underneath every week is the same: read the log (NOTE / WARNING / ERROR), check the row counts after a join, confirm variable types, check NMISS, and validate before you trust output. Remember that the wellness-program study is synthetic and observational — a result is not a real health finding, the arm difference is associational (the synthetic arms are not described as randomized), an odds ratio is not a risk ratio, and “statistically significant” is not “practically important.”
Again: this page is a pacing plan to help you read ahead. For the real calendar — every date, every deadline, every submission window, and any adjustment during the term — Blackboard (the LMS) is authoritative.
Verification & reproducibility status
verified: false. This is a shell pacing page and carries no executed analysis. The weekly notes it links to contain SAS code, log excerpts, and numeric results (means, t/F statistics, p-values, regression coefficients, odds ratios, and the simulation summaries) that are hand-authored, synthetic, and were NOT run — SAS is proprietary and is not executed in this build. The few quantities named on this page (the locked join counts 594 inner / 596 left, the simulation power ≈ 0.99 and Type I ≈ 0.05) are the study’s locked synthetic values, not confirmed results. The course SAS execution/output gate is BLOCKED; a rendered code block or typed listing is not evidence the code runs or the numbers are right. Do not treat any value as a confirmed reference until the human/SAS-run sign-off in the course’s private notation and verification ledger §5 is complete.
Public vs. graded
These notes, the SAS examples, and the practice here are public and ungraded — study material only. No graded prompts, answer keys, rubrics, point values, or due dates appear on this site. Graded SAS workflow checkpoints, skill checks, homework, analytics labs, the midterm practical, the final analytics project, and the final practical live in Blackboard (the LMS), which is authoritative for due dates, submissions, and grades. If this page and Blackboard ever disagree, follow Blackboard.