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🌱 SAS Learning Roadmap — Stages 1 → 6

A forward-thinking, traditional guide — learn what matters, then touch SAS.

Contents

• Stage 1 — Foundations
• Stage 2 — SAS Basics
• Stage 3 — Core Skills
• Stage 4 — Analytics
• Stage 5 — Advanced SAS
• Stage 6 — Best Practices
• Recommended Resources
• Formatting & Style

Stage 1: Foundations

Before touching SAS, ground yourself. In the old way — patient, meticulous — learn these pillars so the language feels like an old friend rather than an alien code.

• Basic statistics — mean, median, variance, regression, distributions. Know what summary numbers tell you about data.
• Data structures — tables, rows, columns. Think relationally: each row tells a story; each column holds a truth.
• Programming logic — variables, loops, conditions. Flow control is the quiet muscle beneath every analysis.

A skeptical question to keep: if a number is telling you a story, who wrote the first draft? Always ask where the data came from.

Stage 2: Learning SAS Basics

Begin with the essentials. Install, open, and befriend SAS Studio or SAS OnDemand for Academics. Learn to run small programs before attempting grand experiments.

Environment & Setup

SAS University Edition has historically been popular; SAS OnDemand is the modern free cloud option. Open SAS Studio, create a new program, run it.

DATA Step — the heart

Used to read, clean, and manipulate data. The DATA step is where rows are born and filtered.

DATA mydata; SET sashelp.class; /* copies an inbuilt dataset */ WHERE age > 12; /* filters */ RUN;

PROC Step — procedures

Procedures analyze or summarize: light, purposeful, and often short.

PROC MEANS DATA=sashelp.class; VAR height weight; RUN;

Input & Output

Reading external files: PROC IMPORT for Excel/CSV, INFILE for text. Export with PROC EXPORT.

Stage 3: Core Skills

• Data Cleaning — IF, WHERE, KEEP, DROP, RENAME.
• Merging & Appending — SET and MERGE statements.
• Formatting — PROC FORMAT for readable values.
• Sorting & Summarizing — PROC SORT, PROC FREQ, PROC SUMMARY.

Practice: pick a CSV, clean missing values, rename columns into a tidy naming convention, and save the cleaned dataset.

Stage 4: Analytics

Now the tools grow teeth. Apply statistical procedures to questions that matter.

• Regression — PROC REG, PROC GLM.
• Time series — PROC ARIMA.
• Logistic regression — PROC LOGISTIC.
• Survival analysis — PROC LIFETEST.

Stage 5: Advanced SAS

• Macros — automate repetition.
• PROC SQL — use SQL in SAS for flexible joins and queries.
• SAS Functions — dates, strings, arrays.
• Efficiency — indexing, performance tuning.

Stage 6: Best Practices

Tradition meets craftsmanship: comment, document, and format with care.

• Always comment your code. Explain why, not just what.
• Readability over terseness — future you will thank present you.
• Document changes and follow naming conventions.
• Debugging — learn PUTLOG and how to read the SAS log well.

Recommended Resources

Books & courses that stood the test of time:

• The Little SAS Book — Lora D. Delwiche & Susan J. Slaughter (classic, beginner-friendly).
• Learning SAS by Example — Ron Cody.
• SAS official free courses (SAS OnDemand). Coursera / edX beginner tracks.
• Practice with built-in datasets: sashelp.class, sashelp.cars.

Formatting, Style & Examples

Below: concise examples showing bad & good. The old maxim holds: clarity beats compactness.

1. Avoid multiple statements on one line

Data Urate_ny; Set Urate_US; if state='NY'; Run;

Data Urate_ny; Set Urate_US; If State='NY'; Run;

2. Formatting lists of variables (SQL in SAS)

Proc sql; CREATE table health_plan_choices as SELECT Company, Job, Health_plan FROM library.occ_source WHERE quarter_begin <= &Mquarter and quarter_end >= &Mquarter; quit;

Proc sql; CREATE table health_plan_choices as SELECT Company, Job, Health_plan FROM library.occ_source WHERE quarter_begin <= &Mquarter and quarter_end >= &Mquarter; quit;

3. Use comments for maintainability

Proc sql; CREATE table health_plan_choices as SELECT Company, Job, Health_plan, Worker_id /* added March 4th by Abigail Hammond */ FROM library.occ_source WHERE quarter_begin <= &Mquarter and quarter_end >= &Mquarter; quit;

Why these practices matter: readability, easier debugging, maintainability, and meeting professional standards.

Quick Exercises

1. Open SAS Studio and run the PROC MEANS example on sashelp.class.
2. Create a DATA step that keeps only numeric variables from a CSV and exports a cleaned CSV.
3. Rewrite a messy PROC SQL statement into the formatted good practice style above.

A final skeptical note: every result invites another question. The method is the map — but do not mistake the map for the land.

Made with care — follow tradition, ask questions, stay curious.